{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DAY8 感知机\n",
    "\n",
    "感知机（Perceptron）是一种二分类的线性分类模型，由美国心理学家罗森布拉特（Frank Rosenblatt）在1957年提出。感知机的基本思想是通过对输入向量进行加权求和，然后通过一个阈值函数（通常是阶跃函数）将结果映射到不同的类别。\n",
    "\n",
    "感知机的输入是一个固定长度的向量，每个输入特征都与一个权重相关联。感知机通过将输入向量的每个特征与相应的权重相乘，然后将所有加权的结果求和，得到一个标量值。如果这个标量值大于等于阈值，则感知机将被分类为一个类别，否则将被分类为另一个类别。\n",
    "\n",
    "感知机的训练过程是一个迭代的过程。初始化权重为随机值，然后将训练样本输入感知机进行分类。如果感知机分类错误，则根据误差调整权重。这个过程不断迭代直到所有训练样本都能正确分类或者达到事先设定的迭代次数。\n",
    "\n",
    "感知机具有以下特点：\n",
    "\n",
    "1. 简单而高效：感知机是一种简单的线性分类模型，计算效率高，适用于大规模数据集。\n",
    "2. 二分类：感知机只能解决二分类问题，无法处理多分类问题。\n",
    "3. 线性可分性：感知机的分类能力受到线性可分性的限制，即只能对线性可分的数据集进行有效分类。\n",
    "4. 学习策略：感知机使用的是在线学习策略，即每次只使用一个样本进行权重的调整，而不是批量处理所有样本。\n",
    "\n",
    "感知机为后续神经网络的发展奠定了基础，尤其是在单层神经网络中具有重要的作用。它的简单性和可解释性使得它成为机器学习领域的重要里程碑之一。然而，在处理复杂问题时，感知机的能力受到限制，需要更加复杂的模型和算法来解决。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1: Import Libraries and Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.linear_model import Perceptron\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the Iris dataset\n",
    "iris = load_iris()\n",
    "\n",
    "# Extract the features (sepal length and sepal width)\n",
    "X = iris.data[:, :2]\n",
    "y = iris.target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2: Preprocess Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standardize the features\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3: Train the Perceptron Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      ],
      "text/plain": [
       "Perceptron()"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a Perceptron object and fit the model\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 4: Plot the Decision Boundary and Data Points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OO+00LrvssrjHcvv27YwaNarZBKOmx6upgz1eEydO5Pjjjw9fvuCCC6isrOQXv/gFl1xyCbm5uWzfvh3DMBg5cmTEbQcMGEBmZmazmFqjpfhD+z7w9ZKbmxuRAII1BvyBBx7gr3/9K1u3biUYDIavCw3laSra8zUzM5PTTz+dZ599lrvvvhuwhhIMGjQoPLY9ls7+20UT7TEd6MILL+Sxxx7jyiuv5Be/+AXHHXcc55xzDuedd95BT2yrqakBIC0tLbzttdde4ze/+Q0rV66MGEOdaO3a+vp6FixYwOOPP87u3bsjhklUVlaGf7/rrrs488wzGT16NBMmTODkk0/m+9//frgiSWte80LEI0ms6NVmzJgRMUO+KdM0UUrx5ptvYrPZml0f6skIaetMetM06d+/f8yan7m5uW3abzztMes/2jEBYo7vS9SuXbuorKwMJ2KhHqibb765We9xyIFJW2vdcMMNnH766fz3v//l7bff5rbbbmPBggUsXryYqVOnHtS+QzrieB133HG89tprfPHFF+Exi5B40hFN04SyqfaM/3e/+x233XYbP/zhD7n77rvJzs7GMAxuuOGGqD2OsZ6vl112GQsXLuTTTz9l4sSJvPrqq/z0pz9t98oFHfG3S+Q1mJSUxNKlS/nggw94/fXXeeutt3jhhRc49thjeeedd2LGlYg1a9YAja+djz76iDPOOINjjjmGv/71r+Tn5+NwOHj88cd59tlnE9rnddddx+OPP84NN9zAkUceSUZGBkopLrroooi/6zHHHMOWLVt45ZVXeOedd3jssce47777ePjhh7nyyis75TUv+gZJYkWfNWLECLTWFBYWhns627KPZcuW4ff7Y04AGTFiBO+99x5HH310Qh9soV6KponKxo0bAcKTkNqSxAwbNoxvv/222fYNGzaEr+8MTz31FED4w2v48OGA1fPdtCcymhEjRoQ/nFtrxIgR3HTTTdx0001s2rSJKVOmcM899zSrkhAybNgwVq1ahWmaEUlTZx6vQCAANPaqDRs2DNM02bRpU8TklqKiIioqKiJiysrKoqKiImJ/Pp+PvXv3timW0L43bdoU/psBlJSUNOuxfPHFF5k7d26zSWkVFRUxJ99Fc/LJJ5Obm8szzzzD4YcfTl1dHd///vcTirWr/3aJMgyD4447juOOO457772X3/3ud9x666188MEHLb4eYqmpqeHll19myJAh4efJSy+9hNvt5u2338blcoXbPv74481uH+v95cUXX+Tyyy/nnnvuCW/zeDzNnmcA2dnZzJ8/n/nz51NTU8MxxxzDHXfcwZVXXtmq17yscCbikTGxos8655xzsNls3Hnnnc16XLTW7N+/v8V9nHvuuZSWlvLQQw81uy60zwsuuIBgMBg+JdpUIBBo9gGwZ8+eiFnmVVVV/Otf/2LKlCnh098pKSkAUT88YjnllFP44osv+Oyzz8Lbamtr+fvf/05BQQGHHHJIwvtqq8WLF3P33XdTWFjIpZdeCkD//v2ZM2cOjzzySNQEq2mZp3PPPZdvvvkm6iz8WL1mdXV1eDyeiG0jRowgLS2tWVmqpk455RT27dsXMTs/EAjw5z//mdTUVGbPnh3/wbaD1157DYDJkyeHYwK4//77I9qFito37a0dMWIES5cujWj397//PWZPbEuOP/54HA4Hf/7znyOO9YGxgNWzeeDfY+HCha0e52i327n44ov597//zRNPPMHEiRMTWiSjO/ztElFWVtZs25QpUwDiPjfjqa+v5/vf/z5lZWXceuut4STQZrOhlIr4+2/bti3qylwpKSlR31ui/V3//Oc/N3tOHfjemZqaysiRI8OPqTWv+ba814m+Q3piRZ81YsQIfvOb33DLLbewbds2zjrrLNLS0ti6dSsvv/wyP/7xj7n55pvj7uOyyy7jX//6FzfeeCNffPEFs2bNora2lvfee4+f/vSnnHnmmcyePZurrrqKBQsWsHLlSk488UQcDgebNm1i4cKFPPDAAxFF7kePHs0VV1zB8uXLycvL45///CdFRUURPSZTpkzBZrPxhz/8gcrKSlwuF8cee2zMcbcAv/jFL3juueeYN28e119/PdnZ2Tz55JNs3bqVl156qd1P0b755pts2LCBQCBAUVERixcv5t1332XYsGG8+uqrEQsS/OUvf2HmzJlMnDiRH/3oRwwfPpyioiI+++wzdu3aFa4v+j//8z+8+OKLnH/++fzwhz9k2rRplJWV8eqrr/Lwww+Hk72mNm7cyHHHHccFF1zAIYccgt1u5+WXX6aoqIiLLrooZvw//vGPeeSRR/jBD37AihUrKCgo4MUXX+STTz7h/vvvjxhr2B4++uijcLIdekwffvghF110EWPHjgWsZPbyyy/n73//OxUVFcyePZsvvviCJ598krPOOou5c+eG93fllVfyk5/8hHPPPZcTTjiBb775hrfffrtVPaFN5ebmcvPNN7NgwQJOO+00TjnlFL7++mvefPPNZvs87bTTuOuuu5g/fz5HHXUUq1ev5plnnonowU3UZZddxoMPPsgHH3zAH/7wh4Ru09l/u7a66667WLp0KaeeeirDhg2juLiYv/71rwwePDhiAmYsu3fvDp9JqKmpYd26dSxcuJB9+/Zx0003cdVVV4Xbnnrqqdx7772cfPLJXHLJJRQXF/OXv/yFkSNHsmrVqoj9Tps2jffee497772XgQMHUlhYyOGHH85pp53GU089RUZGBocccgifffYZ7733XrNxzocccghz5sxh2rRpZGdn8+WXX/Liiy9y7bXXhtsk+ppvy3ud6EM6vR6CEJ0gkTJPIS+99JKeOXOmTklJ0SkpKXrs2LH6mmuu0d9++224zezZs/X48eOj3r6urk7feuuturCwUDscDj1gwAB93nnn6S1btkS0+/vf/66nTZumk5KSdFpamp44caL+f//v/+k9e/aE24TK5rz99tt60qRJ2uVy6bFjx0aU8Al59NFH9fDhw7XNZosoQROv9M6WLVv0eeedpzMzM7Xb7dYzZszQr732WkSbaGWDtG5euiqW0LEP/TidTj1gwAB9wgkn6AceeCBc3ihabJdddpkeMGCAdjgcetCgQfq0007TL774YkS7/fv362uvvVYPGjRIO51OPXjwYH355Zfr0tLSqHGWlpbqa665Ro8dO1anpKTojIwMffjhh+t///vfEfs9sMSW1loXFRXp+fPn6379+mmn06knTpzY7PGH7i9aCS9ilLlqKlqJLafTqceOHat/+9vfap/PF9He7/frO++8M/x8GzJkiL7lllsiShVprXUwGNT/+7//q/v166eTk5P1SSedpDdv3hyzxNaBr5VQXE1LGwWDQX3nnXfq/Px8nZSUpOfMmaPXrFnTbJ8ej0ffdNNN4XZHH320/uyzz5od41jPtQONHz9eG4ahd+3aFbddU535t4tWYita2awDS2y9//77+swzz9QDBw7UTqdTDxw4UF988cV648aNLT6+UCk9QCuldHp6uh4/frz+0Y9+pJctWxb1Nv/4xz/0qFGjwu8rjz/+eLOYtNZ6w4YN+phjjtFJSUkR5dPKy8vDxzQ1NVWfdNJJesOGDc3+/r/5zW/0jBkzdGZmpk5KSor5XE70NR/rvU4IpfVBztIQQrSbgoICJkyYED6NLISAqVOnkp2dzfvvv9/VoQghuhEZEyuEEKLb+vLLL1m5ciWXXXZZV4cihOhmZEysEEKIbmfNmjWsWLGCe+65h/z8fC688MKuDkkI0c1IT6wQQohu58UXX2T+/Pn4/X6ee+65iImAQggBIGNihRBCCCFEjyM9sUIIIYQQoseRJFYIIYQQQvQ4fWpil2ma7Nmzh7S0NFnKTgghhBCiG9JaU11dzcCBA+MuxNOnktg9e/YwZMiQrg5DCCGEEEK0YOfOnQwePDjm9T02if3973/PLbfcws9+9rOoa3dHE1pq8Odn78DlSO/A6IQQQgghRFt4/VXc9/LQFpeI7pFJ7PLly3nkkUeYNGlSq24XGkLgcqTjliRWCCGEEKLbamnoZ4+b2FVTU8Oll17Ko48+SlZWVleHI4QQQggh2tFbozwJtetxSew111zDqaeeyvHHH99iW6/XS1VVVcSPEEIIIYTofhaN9bDmoRUM+/H6hNr3qOEEzz//PF999RXLly9PqP2CBQu48847OzgqIYQQQghxMJ6+ei9Txu9BKRiX6uCVBG7TY3pid+7cyc9+9jOeeeaZhJcfvOWWW6isrAz/7Ny5s4OjFEIIIYQQiQr1vk4Zvwe3A8anOBK+bY/piV2xYgXFxcUceuih4W3BYJClS5fy0EMP4fV6sdlsEbdxuVy4XK7ODlUIIYQQQiSgcm45bgeMdCWevIb0mCT2uOOOY/Xq1RHb5s+fz9ixY/nf//3fZgmsEEIIIYTovkJDCNqqxySxaWlpTJgwIWJbSkoKOTk5zbYLIYQQQojuadFYD4XXrmUKtLkXFnpQEiuEEEIIIXq2phO4WjP+NZoencQuWbKkq0MQQgghhBAtaK/e16Z6dBIrhBBCCCF6hvbofW1KklghhBBCCNFhDnYCVyySxAohhBBCiHbXEUMImpIkVgghhBBCtKtQAtveQwia6jErdgkhhBBCiJ6jIxNYkJ5YIYQQQgjRjkJjYF0dnGVKEiuEEEIIIQ5aKHmd2sE9sCGSxAohhBBCiDbr6AlcsUgSK4QQQggh2qQzJnDFIhO7hBBCCCFEm3VFAgvSEyuEEEIIIdqgsyZwxSJJrBBCCCGESFhnT+CKRZJYIYQQQgjRoq6awBWLJLFCCCGEECKurpzAFYtM7BJCCCGEEC3qTgksSE+sEEIIIYSIo6sncMXSzcIRQgghhBDdQWgIQVdP4IpFklghhBBCCBEWSl4L6R4TuGKRJFYIIYQQQoRVzi3vduNfo5GJXUIIIYQQArB6Ybvj+NdoekCIQgghhBCio4UmcHXnIQRNSRIrhBBCCNGHdfcJXLFIEiuEEEII0Qf1lAlcsUgSK4QQQgjRB/WUCVyxyMQuIYQQQog+pidN4IqlB4cuhBBCCCFaq6dN4IpFklghhBBCiD6gp07gikWSWCGEEEKIXqynT+CKRZJYIYQQQoherKdP4IpFJnYJIYQQQvRSvWECVyy98CEJIYQQQojQBC6les8QgqYkiRVCCCGE6EV62wSuWCSJFUIIIYToBXrrBK5YJIkVQgghhOgleuMErlhkYpcQQgghRA8X6oXtS6QnVgghhBCiB2s6gauv9MKCJLFCCCGEED1SX5nAFYsksUIIIYQQPUhfm8AViySxQgghhBA9TF8bOhCNTOwSQgghhOgh+uIErlikJ1YIIYQQogfoqxO4YpEkVgghhBCiG+vrE7hikSRWCCGEEKKbWvPQij4/gSsWSWKFEEIIIbqhRWM9DJfe15gkiRVC9E2OII6pRTinFqMyvOC14V/bD98X+egqV1dHJ4To42QCV8skiRVC9D2uAMkXr8foXwfKKlVDUhDHoUU4JpRS9+w4zOKUro5SCNFHyQSuxEiJLSFEn+OavROjfx3KaEhgGygDcAZJOmsToLsqPCFEH7VorIc1D61g6oQ9TEh1SALbAumJFUL0Lc4AjoklVsIahTJAZXuxDasiuD2jc2MTQvRZod5XmcCVOOmJFUL0KUaOB+WI38uqTbDl13ZSREIIYZmQ6pAEthWkJ1YI0bcEVcttAJ1gOyGEOBihCVxTAJAEtjUkiRVC9ClmSTJmjQOV4o8YD9uUMiD4XWanxiWE6HtkAtfB6THDCf72t78xadIk0tPTSU9P58gjj+TNN9/s6rCEED2NVviW5cdMYLUJgS0ZmPuTOjcuIUSf8vTVe2UC10HqMUns4MGD+f3vf8+KFSv48ssvOfbYYznzzDNZu1ZqqAkhWse/fAC+L/MA0EFrmzat/829KdS/OrKLIhNC9AWLxnqYMn4PLjkfflB6zOE7/fTTIy7/9re/5W9/+xuff/4548ePj3obr9eL1+sNX66qqurQGIUQPYXC+14B/tW5OCYVY2R50fV2/OtyrGEEWsbDCiE6RtMhBDKJ6+D0mCS2qWAwyMKFC6mtreXII4+M2W7BggXceeednRiZEKInMYtS8L5b2NVhCCH6gKYTuKSMVvvoUUns6tWrOfLII/F4PKSmpvLyyy9zyCGHxGx/yy23cOONN4YvV1VVMWTIkM4IVQghhBACkAlcHaVHJbFjxoxh5cqVVFZW8uKLL3L55Zfz4YcfxkxkXS4XLpesgS6EEEKIrhFKYCekSvLa3npUEut0Ohk50ppwMW3aNJYvX84DDzzAI4880sWRCSGEEEI0F1qFS7S/HpXEHsg0zYiJW0IIIYQQ3YFM4Op4PSaJveWWW5g3bx5Dhw6lurqaZ599liVLlvD22293dWhCCCGEEIBM4OpMPSaJLS4u5rLLLmPv3r1kZGQwadIk3n77bU444YSuDk0IIYQQQiZwdbIek8T+4x//6OoQhBBCCCGikglcna/HrNglhBBCCNFdyQSuztdjemKFEEIIIbobmcDVdSSJFUIIIYRoJZnA1fUkiRVCCCGEaAWZwNU9SBIrhBBCCJGgRWM94fGv0vvatWRilxBCCCFEgirnlsv4125CemKFEEIIIVoQGkIwVYYQdBuSxAohhBBCxCATuLovSWKFEEIIIaKQCVzdmySxQgghhBAHkAlc3Z8ksUKI7ssVwDGhFNvQKgCCO9Pxr+4HXnnrEkJ0LJnA1f3JJ4EQoluyDaki6bxvwWmCtrbZR5fjmrWT+pfGENyR3rUBCiF6JZnA1XNIiS0hRLej0rwknf8tOEyUAmU0/CjAYZJ0/reodG9XhymE6EUWjfWw5qEV4SEEksB2f9ITK4TodhxTisFuoqJ8zVYGaEwcU4rxLR3S+cEJIXodmcDVM0lPrBCi27GPLo+awIYoA+yjyzovICFEr9V0ApcksD2LJLFCiG5H2cwE2uhOiEQI0dvJBK6eS4YTCCG6neCeVFSGF2WLfr0OQnBvSucGJYToVWQCV88nSawQotvxfZWHY8L+mNcrG/i/GtCJEQkhegtZgav3kCRWCNHtmHvS8H40CNes3WiT8PjY0O/ejwcR3JXWtUEKIXocmcDVu0gSK4TolnyfDCa4LwXnjL3YhlQDENyZhm95PsHNWV0cnRCip5Le195DklghRLcV3JJF/ZYswqsdoLoyHCFEDxbqhZUEtveQJFYI0QNI8iqEaBuZwNV7SRIrhBBCiF5HJnD1fpLECiGEEKJXkQlcfYMksUKICCrJj318KUa6D13nwL8uB13l6uqwhBCiVaT3tfeTJFYIEeaYsQfX7F2gNGgFSuOcvRP/ijy87w+ztgkhRDcW6oUVvZ8ksUIIAByTi3Efu7PJlsZlXR3TitB+A9+HQzs/MCGESEBoDKxM4Oo7JIkVQlg9rjN3oTWoKJ2tSoHzsH34Ph8IXnnbEEJ0H6HktRAZQtDXyKeREAIjvwYjzR+3jbJr7CPLCazN7aSohBAiPpnA1bdJEiuEQDmDLbbRGpTT7IRohBAicdL72ncZXR2AEKLrmeXuFtsoBWZZy+2EEKIzyAQuIT2xQgh0pZvA1nRsw6pQUb7aahN0lZPg9vTOD04IIZqQCVwiRHpihRAAeN4pAK8NfcDIAm0CpsLz+ghk+VchRFd6+uq9FF67FrdDElghSawQooEuT6L2yQkE1udYiSvWONjgdxnUPTWe4E7phRVCdD0ZAytCZDiBECJMV7jxvDYS3ilApQTQ9TbwyIeFEKJrhYYQTOnqQES3IkmsEKI5nx3tk7cHIUTXC03gkh5YcSD5lBJCCCFEtyMTuERLJIkVQgghRLcSSmCl91XEI0msEEIkyh7EPqIClRzArHIS3JoBpsyPFaK9Vc4tRylJYEV8ksQKIUQCHIfuwzV7F8oVtFYvU2DW2vG+U0Dg25yuDk+IXqHpBC6XZCiiBfIUEUKIFjgO3Yf7xO3hy6qhXK5KDuA+azOe/ygCm7K7KDohegeZwCVaS5JYIYSIxx7ENXtX1KuUsmrpuo7dQWBTFrIYhBCtJxO4RFvJYC4hhIjDPqIS5QrGvF4pMLK8GANqOzEqIXqHphO4JIEVrSVJrBBCxKGS/GidQLvkQMcHI0QvIxO4xMGQ4QRCCBGHWe0Mj4GNR1c7Oz4YIXoJmcAl2oM8dYQQIo7g1gzMWjsqORA1mdUmmMXJmCXJnR+cED1QaAKXkjGw4iBJEiuEEPGYBt53CnCftTlcWitEm4BWeN8r6KrohOgxZAKXaG8yJlYIIVoQ+DaH+pdGo8vdEdvN4mTqnxtHcFdaF0UmRM8gE7hER5CeWCGESEBwcxa1mzMx8upQKX50lROzVIYQCJEImcAlOoIksUIIkTCFWZTS1UEI0WPIBC7RkXrMcIIFCxZw2GGHkZaWRv/+/TnrrLP49ttvuzosIYQQQkTx9NV7Kbx2LUrBhFSH9MKKdtdjktgPP/yQa665hs8//5x3330Xv9/PiSeeSG2tFBgXQgghuotFYz2seWgFUyfsYUKqQ8bAig7TYzr333rrrYjLTzzxBP3792fFihUcc8wxXRSVEKLV7AHsE/ajnEGrfFWJnJ4XojepnFuO2yHjX0XH6zFJ7IEqKysByM7OjtnG6/Xi9XrDl6uqqjo8LiFELCbuczdhH1kRLlOl9U50tYP6hWMkmRWiFwjVgBWiM/SY4QRNmabJDTfcwNFHH82ECRNitluwYAEZGRnhnyFDhnRilEKIppJ/sBbHqIqIOqtKgUrzkzx/DSq7ruuCE0IclNAQginj90gvrOg0PTKJveaaa1izZg3PP/983Ha33HILlZWV4Z+dO3d2UoRCiKZsheXYBkRPUpUCFLhP+65zgxJCtAuZwCW6So8bTnDttdfy2muvsXTpUgYPHhy3rcvlwuVydVJkQohYnLN2N1vtqimlwJZfC5j00O/WQvQ5sgKX6Go95tNCa821117Lyy+/zOLFiyksLOzqkIQQCTJS/C22UQpICnR8MEKIdhGawCUJrOgqPaYn9pprruHZZ5/llVdeIS0tjX379gGQkZFBUlJSF0cnhIhHe23E6IRtbKOB+h7zliREnyYTuER30GN6Yv/2t79RWVnJnDlzyM/PD/+88MILXR2aEKIFvi/zYg4lACuBNfe76UFvSUL0STKBS3QnPabbQ2vd1SEIIdoosCoXc9YuVGqgWTIbeml73ino9LiEEIkL9b4qGQMruokek8QKIXoyg9p/TCb5sjUYWY21m5UCggrPa8Mxd2R0XXhCiJhkApforiSJFUJ0Do+dur9PwcirxTltHziCBHdk4P86FxlGIET3JStwie5KklghRKcyi1LwvDGiq8MQQiRAJnCJ7qxVSaxpmnz44Yd89NFHbN++nbq6OnJzc5k6dSrHH3+8rIglhBBC9AKhIQRTQHphRbeV0Dm8+vp6fvOb3zBkyBBOOeUU3nzzTSoqKrDZbGzevJnbb7+dwsJCTjnlFD7//POOjlkIIYQQHURW4BI9RUI9saNHj+bII4/k0Ucf5YQTTsDhaP6E3r59O88++ywXXXQRt956Kz/60Y/aPVghRBs5fdiGVWPWOtB70rs6mu7FHkSlBNAeG3hlhJXou5r2vk5I7Z6Jq9ImabqOIAa1Kin2MoBt5NR+krSHeuXGp7rnMRCNEnrHfueddxg3blzcNsOGDeOWW27h5ptvZseOHe0SnBDiIOXUkXLxelRKY2krbYJ/bQ7e10d2bWxdTKX6cM7chWNCKcqu0RqCWzPwfjwIc09aV4cnRKfrzhO4bDrITN8qDvNtIEV7ACgyMvnYNZk1juEHvf9+wQrmeL9mXGA7BpogivX2YSxxHcp+m1RO6a4SSmJbSmCbcjgcjBghkzaE6HJZdaReuRo4oLNCgXPifoxML/XPjO+a2LqYSvOSfNlaVIof1TCoSimwFVSSPKyK+oWjCW7L7NIYhehM3XkCl6GDXFL3LgXBvRFjIHPNCs6t/5Ass4qPXFPavP+84H7m176BnSAGVuFqG5pxge2MCuzmnymnUGzLPrgHITpEQknsqlWrEt7hpEmT2hyMEKL9pFyyAWh+tk0pa4EB2+AayKuGor7X6+iauwOV3JjAhigDtKlxn76F2r9MBVNKf4nerSdM4DrUv5HC4N5mS1eHXp3Her9mnb2A/bbMNu3/jPqPcTRJYENsaBQBTq//hH+knt6mfYuOlVASO2XKFJRSaK1RLYw/CQaD7RKYEOIg2IKoVH/M4WKhRDb51O+o++fkzo2ti6kkP/axZc0S2PD1BqiUAPYRFQQ2Se+L6L16ygpch/nWx70+iGKafyPv2Ga0et8DgqUMNMtiXm+gGWyW0j9YJr2x3VBCSezWrVvDv3/99dfcfPPN/M///A9HHnkkAJ999hn33HMP//d//9cxUQohWsUYUJvQfAeV7u/4YLoZlemNmcCG6CAYOfWwqXNiEqIz9YQJXE3lmFXNemGbsqHpF6xo0777mZUJt5MktvtJKIkdNmxY+Pfzzz+fBx98kFNOOSW8bdKkSQwZMoTbbruNs846q92DFEK0jlmT4AdTsH1n9vYI/gSGCBig/baOj0WILtLde1+b8mPHRuwv3CaqzZUEfCR2O5+sDdUttXrA1+rVqyksLGy2vbCwkHXr1rVLUEKIg1SZhA5aQwZiUQr8q/t1XkzdhFmahFnmintsAAIbszonICE6UagGbE+y1lFIME5frIFmnaOgTfveas/H20KC6sHBNnt+m/YvOlark9hx48axYMECfD5feJvP52PBggWtqmIghOhYvi/zgOiJrNbWKXPfksGdHFV3oPB+NDjmcAttgn9VLrra1blhCdGBFo31sOahFUwZvwe3o+f0wgJ85hyPiYEZJZENoigxMthgH9qmffuVg09cE+O2+dg1iYCSntjuqNV/lYcffpjTTz+dwYMHhysRrFq1CqUUixYtavcAhRBt4/ugACPLi31URUQiqxRgQs3jE4C+eco8sL4fnuQArmN3gNKgFSiNMiCwLgfvOwVdHaIQ7SY0BrYnDSFoar8tk2eST+SCusUk4yWIAWhsaIqNLJ5LPh5Ttf297CPnZFzaz1G+NWgUGtXwr+YT50Q+ccZPckXXUVq3dFKtudraWp555hk2bLBK+IwbN45LLrmElJSUdg+wPVVVVZGRkcEvLqjA7ZBVi0QfkVlP0ulbMDK9EFT4Vubi/3RIV0fVLagkP/bxpRiZXrTHTmB9Dub+pK4OS4h2tWish+HXre2RCWxTNh3gkMB2BgZLCWKwyT6Y7bYB7bZqV7pZwyT/d6TqOqpVMqsdw6kyUttl36J1PFU1/D5nJpWVlaSnx87X2pTE9lSSxAohhOhLQmW0umsNWCGiSTSJbVMl76eeeoqZM2cycOBAtm/fDsB9993HK6+80rZohRBCCNFunr56L2seWsHUCXuYkOqQBFb0Sq1OYv/2t79x4403Mm/ePMrLy8OLG2RlZXH//fe3d3xCCCGESFBPnsAlRGu1Oon985//zKOPPsqtt96K3d44L2z69OmsXr26XYMTQgghRGKaTuCS3lfRF7S6OsHWrVuZOnVqs+0ul4va2tp2CUoI0U4ME8ekEhzTiqwVqAIGgQ3Z+L7IxyxNPujdq3QvzsP24ZhQAq4gusqF/+v++L7KgyiLBRh5tTgP24t9dDnYTcziZHxf5RFYnWtVCBBCHJSeWoFAiLZodRJbWFjIypUrI1bxAnjrrbekTqwQ3YlhknTuRmzDrWUVlQKcJvbxpdgP2U/9i6MJbsts++5z60i+dB04g43LuGZ4cc7eiX18KXXPHALexrcY+6gy3GdvAg2hajhG/zrc87YSGF6B55VRksgK0UahCVwuKWcq+pBWP91vvPFGrrnmGjweD1prvvjiC5577jkWLFjAY4891hExCiHawHnYPmyFlc2qzygbaFOTdPYmah46NGqPacus20cksDQkygqMfvW45uzA+/Zw6wp3APeZm0ER2b7hd/uYchxTivF/ndeGWITou0LJ61TpgRV9UKuT2CuvvJKkpCR+9atfUVdXxyWXXMLAgQN54IEHuOiiizoiRiFEq2kc0/cRa6VGZYB2mjgO2Y//m/6t3rttaBVGtifm9coAx8RSvEuGgteOY2IJGDpuOUfH9H2SxAqRoND41ykg5bNEn9WmEw+XXnopl156KXV1ddTU1NC/f+s/BIUQHUclBTDS/PEbmWAMqIVvWr9/Y0At2ozsVW0Wg11j5NRj7knDNiD+eHmlwJbjAbsJgTZV/hOiT6mcWy7jX0Wf1+pPi7vuuovFixcDkJycHE5ga2trueuuu9o3OiFEm2gzkbGlChJqF4WZ4FtHsKFdUEELy6poDZhtC0eIvmTRWI+MfxWCNiSxd9xxB/PmzePee++N2F5TU8Odd97ZboEJIQ6C105wTwo6TlKobJrAlsw27T7wXUbcXlgAs9aOWZLU0D6TeEubaxOC29ITT46F6KOevnovhdeulSEEQtDGFbv+9a9/8bvf/Y758+fj8/naOyYhRDvwfT4wZqKpgxAsdRP8LqNN+9ZlSfg3ZcZNkn3LBoaT0sDGLMwKJzoYva0yGtoLIaKSFbiEaK5NSezcuXNZtmwZy5YtY86cORQXF7d3XEKIgxTYmI1n8VC0Jpxshv+vdFH/77HEnPmVAM9rIwjuSbX215Cchv73reiP/4sBjY1Ng7oXxqFrnOE4QnFpDZ63Cwhua1tCLURvJitwCRFbq0fUqIbpxSNGjODzzz/nggsuYNq0aTz88MPtHpwQ4uD4v8gnsDEL55RijNw6tM9GYGM2gW+zDv7UvddO/TOHYCusxHFIKSopgFnhwr+qP2ZRSrPmutxN7aOTsY/dj31kOcphEixKwf9Nf3Sl6+BiEaKXkglcQsTW6iRW68bZGenp6bzxxhvccMMNnHXWWe0ZlxCinegKt1XqqkN2rgh+l0nwu8zE2gcMAmtyCazJ7Zh4hOhFZAKXEPG1+qXx+OOPk5HReNrPMAwefPBBpk6dytKlS9s1OCGEEKIvCi1iIBO4hIhN6aZdq71cVVUVGRkZ/OKCCtyO9K4ORwghhIgQSl5lCIHoyzxVNfw+ZyaVlZWkp8fO1xLqiX3wwQf58Y9/jNvt5sEHH4zZTinFdddd1/pohRBCiD5MVuASovUSSmLvu+8+Lr30UtxuN/fdd1/MdpLEip5BYxteiWNqEbacerTPhn9dP/zf5IK38wefqTQvjqnF2EeVg83E3J2K76sBmHtTo7Y3+tfiOLQI29BqMCH4XSa+r/LQFe5OjlwI0V7aOoFraGAf030bGGiW4sfOBvswVjjHUGMkd1CkQnQfCX1ib926NervQvQ4SuM+dQuOCfvDy6ZqDa68HThn7KXumXHo8qROC8c2tJKk8zeCzQzXdDUyvDgm7se7ZDC+zwdFtHdMKcJ10jYwCS8eYGTvwzGtCM9/RxLYlN1psQsh2kebJnBpzXHeFcz0rSaIwtawJF5/XwVH+NbydPJJ7LbLBErRu8nyOKJPcUzfh338foBw0qhUw0+yn+TzN9Li+qjtxR0g6bzIBBYak1PXnF3YCivC240BNbhO2mbF2mT1K2UAhsZ91mZUurdTQhdCtI+2rsB1SGAbM32rAcIJLICBxkmAS+rexaH97R6vEN1JQt/7brzxxoR3eOBytEJ0G0rjnLE39tUGqGwPtsJKglszOzwcx6QSsJuxV9UywXnYPuobYnFO3wcmEGX5VqVAK41jahG+DzuonJYQot2ExsBObeMEriO9azBRGFG+dBtokvAywb+Vr52j2yNcIbqlhJLYr7/+OuLyV199RSAQYMyYMQBs3LgRm83GtGnT2j9CIdqJSvdipMXvmdBBhW1oVacksfYhVXEXzFIG2IZWhS/bCqoiemCjtbcPq0IWghai+wolr4W0fQKXoYMMNkvjttEohgX38TWSxIreK6Ek9oMPPgj/fu+995KWlsaTTz5JVlYWAOXl5cyfP59Zs2Z1TJRC9EZtX/G1c/cphGg3nbkCl+qsoVFCdJFWj4m95557WLBgQTiBBcjKyuI3v/kN99xzT7sGJ0R70lUuzGoH8SojK5smuLNzaggHdsS/H21CcGda+HJwWzo6GL99YJvUPxaiu2qvFbhMZWO3kYMZp41Cs9024ODuSIhurtVJbFVVFSUlJc22l5SUUF1d3S5BCdEhtMK3PD/21UEwy1wEv8uI2aY9+Vf1A7+BjvFJpAwi4vWtGBDzFas1oBX+lXntH6gQ4qC1dQJXLJ+5JsT8ADcBD05WO4Yf9P0I0Z21Ook9++yzmT9/Pv/5z3/YtWsXu3bt4qWXXuKKK67gnHPO6YgYhWg3/uUDCKzLAQgnj1pbv+t6B/UvjqHTzsl7HNS/NBqCKiKRDfW2epcOJvhdZni7uTcV7zsFVrxNemS1CZgKzysj0ZWuTgldCJGYRWM9rHloBVMn7GFCqqPdFjFYay/kU+cEAIJN3rNMFH4cPJt8An4lCyaI3q3Vy87W1dVx8803889//hO/35okY7fbueKKK/jjH/9ISkpKhwTaHmTZWWHR2EZW4JxahJFTj/baCazLwfdNLng6/01fpXtxHFqEfVQ5ymYS3J2G76s8zN1pUdsbebU4Dt2HfWg1WjcsdrAir1Pr2woh4gtN4IKOXYFrWGAvM3zryQ/uJ6BsrLcX8KVzDNVG9/0sFqIliS4726okNhgM8sknnzBx4kScTidbtmwBYMSIEd06eQ2RJFYIIURnWDTWw/Dr1nbKBC4heptEk9hWDS+32WyceOKJrF+/nsLCQiZNmnTQgQohhBC9SdNeWCFEx2n1mNgJEybw3XffdUQsQgghRI/WdAKX9MIK0bFaXejjN7/5DTfffDN3330306ZNazaMIF63rxBCCNEbHewKXEKI1mt1EnvKKacAcMYZZ6BU44xIrTVKKYLBOIUshRAHTWXV4zpuO7YBdaCtWrKe94dBrTNqe2NwJa45uzAyPRA08G/IxvfRIAhEf/kbebU4JhVjZPjQdQ78a3II7kinS1ZScAVwTCgNr1wW3JmOf3U/8B5koU0h2kl7rMAlhGibVn8SNF29SwjRuRxH7cI1a3fENvu4MlLHleF5o5DA6v4R17nP/hb76IqIba7D9+GcVkTdM+Mw9zapgKA0rpO24pxSYpXwMgATHJNKCGzNoP6lURCIs+5tO7MNqSLpvG/BaRJaeMg+uhzXrJ3UvzSa4I7OqecrREs6awUuIUSkViexs2fP7og4ErJ06VL++Mc/smLFCvbu3cvLL7/MWWed1WXxCNGZjIKKcAKrDugU1Rrcp2yldncquiwZAOesnTjGVETfmU2TfOl6av40ndDQeOeRe3BMthYyUaFcteF/27BK3CdtxfP6yHZ8RLGpNC9J538LdtN6rE0er3aYJJ2/kdpHJ6GrpC6u6DoygUuIrtXqiV0hdXV1bNiwgVWrVkX8dKTa2lomT57MX/7ylw69HyG6I/exO4DmCWzTbe7jdoS3Oafvi7nErlKg7BrHkXutDXYT54y9UfcN1uph9vH7UWnetobfKo4pxVYCG+UdShmAzbTaCNFFQhO4pBdWiK7T6p7YkpIS5s+fz5tvvhn1+o4cEztv3jzmzZvXYfsXojsz+tXHTDJDbIMbln5O86Jc8VZWt3pvHWP34/9sELb8GpQ7/mtXGWArrCSwqn/cdu3BPro8agLbNBb76DJ8S4d0eCxCNCUTuIToPlrdE3vDDTdQUVHBsmXLSEpK4q233uLJJ59k1KhRvPrqqx0RY5t5vV6qqqoifoTosVpIYJUCDKvrVTkS/DJp05H/x6E1qATatQdli5+AW206JxYhQtY8tELKZwnRjbS6J3bx4sW88sorTJ8+HcMwGDZsGCeccALp6eksWLCAU089tSPibJMFCxZw5513dnUYQrQLXWeH5EDM3litwaxwW7+XudEmoKIPPwgx91kl8sySJLRJ/N5PBcF9nbMyX3BPKirD2zg29wA6aLURorMsGuthuPS+CtGttLontra2lv79rdOJWVlZlJRYE0EmTpzIV1991b7RHaRbbrmFysrK8M/OnTu7OiQh2sz35YC4CalS4P1ocMMlg+C22LP3Q2NlPYuHWpdrnQS+zbYS32jtgxDcl4y5t3OSWN9XeTETWLAmnvm/yuuUWISQCVxCdE+tTmLHjBnDt99+C8DkyZN55JFH2L17Nw8//DD5+fntHuDBcLlcpKenR/wI0VP5P8snuNeqPNB0wlbod//GTIIbs8Pb6/8zEl1vQ+vo7b0fDYK6xtqy3ncL0BWuZomsNkF77XgWjaSzasWae9Ks+Bruv2ksAN6PBxHcnRbllkK0L5nAJUT31erhBD/72c/Yu9ea0Xz77bdz8skn88wzz+B0OnniiSfaOz4hRJhB3ZPjcc7diXNKMdppZXS63o53WT7+ZQMjmwfs1P51Cu5Tt2IfVY5uGEOqK5x4PhhKcGNORHNd56D2yQk4p+/DMaUYleoHjw3/6lx8ywegqzu3nJXvk8EE96XgPGwvtiHWhLXgrjR8y/MJbs7q1FhE3/T01XuZOmGPJK9CdFOtTmK/973vhX+fNm0a27dvZ8OGDQwdOpR+/fq1a3AHqqmpYfPmzeHLW7duZeXKlWRnZzN06NAOvW8hugcD3wfD8H0wDDDD22IK2PG8Mqrhghm/LYDXju+Twfg+GYy1wkAXrNLVRHBLFvVbsgivdtDF8Yi+Y9FYD1PG78Eli8MJ0W0d9MszOTmZQw89tD1iadGXX37J3Llzw5dvvPFGAC6//HLpBRZ9UGtHA7W2fXdKGLtTLKK3e/rqvUwZvwelZBlZIbqzhJLYULKYiHvvvbfNwbRkzpw56FjV24UQQoiDEJrANQVwOySBFaK7SyiJ/frrryMuf/XVVwQCAcaMGQPAxo0bsdlsTJs2rf0jFEIIITpY095XGQMrRM+QUBL7wQcfhH+/9957SUtL48knnyQry5pcUV5ezvz585k1a1bHRClEe3MGcByyHyPbg/bZCGzIxixNbrfd20aU4ZyxD+UKYpa58XwwFNprYpRh4jxmF/ahVWgNgY3Z+JcNIOZwAUcQ+7j92PrVo/02AhuzMItil8pSyX7s40sx0nzoOjv+9f3Qle01qcvEPrEUx6QSlN0kuC8F74dDwSMDD1EmaYUbSR+xAQyT2p3DqdgwEcw4tcZaweWuZ8K0r8jpX4K33s26lZMp2Re7okxaRgUTp31FakYVNZXprF5xKNWVme0SS3cjE7iE6JmUbuX5+UGDBvHOO+8wfvz4iO1r1qzhxBNPZM+ePe0aYHuqqqoiIyODX1xQgdsh5bb6Kvv4UtwnbwW7CaYCpVEG+Ddk4XltBAQOImlwB0iZvwojw8+Bryz/qly8bw4/uNjHluI+YwvKaCyVpRTogKLu+TGYuyJrw9pHleE+bQs4Gx4rGmWDwHcZ1P93JPgik0fn4XtwHrPTGoKqrWODAv9X/fG+V2Bta6vMelJ+sBbDHYyMXYN36WD8nw1q+757OGdmKSO//zeS+u/DDBqAwrAF8VVmsvmZq6jfe3ATVycdtpzTLlyI3eHHDNpAaWw2k7VfT+a/T19CwO9s0lpz7KlvcPQJ71uXTANlWJMIP3n3OBa/fgq9aYxyaAiBDB8QovvwVNXw+5yZVFZWxi2P2uo6sVVVVeEFDpoqKSmhurq6tbsTolPZCiuspM5uopS1dGlolSr76HLruoOQMn81Kt0PWAmaarJilnNyCY6ZbV9ww8irxX3mlnD+0HTf2DTJl2yAZF+4vW1QNe6zN4GzyWNtyM9tBZUknb2Jxln/4JhcjGvuTpTNWrkrdGyUAsehxThnH8xiISapP1yDcgWbxw64jtmFfVzpQey/5zIcXkb/8AHcOcXWZZuJYbOOkyOtktE/fABHenmb9z9y3HrO+t6z2B1+lAKbPYitYVnfcZNXcdalz0a0P/r4xcw66T0MQ2MYGps9GP591knvcfTxi9scS3fTtAasJLBC9DytTmLPPvts5s+fz3/+8x927drFrl27eOmll7jiiis455xzOiJGIdqNc+Yu0NGXYlUGOMaWY+TUtWnfRkEFRoYv+r4behxdM/a1ad8ArhO2hfcVbf8ocB+3PbzNedTu2O0NsBdWYQysadigcc7c1az3uOn+ndP3gTvQptgdh+9DNSTTUWMHXHN2tGnfPV325OU4M8tQtubLpSlDY3P6yD18aZv3P/uUt9BaRT32hqEZf+g35PQvAsDu8DHzhHfj7m/mCe9id/jitunuFo31sOahFUwZvwe3Q8bACtFTtTqJffjhh5k3bx6XXHIJw4YNY9iwYVxyySWcfPLJ/PWvf+2IGIVoFyrFh31QbbjnNRptgn1sWZv275qxN2YSCA29j04TI79tZyxs+TVxl50FsI2otH5xBLENr4z/WIPgaHisRn4NRpo//rK2do19RNt6BB0TS1o+Nul+MGKse9uLZU1YEXeYhjJMsictb9O+0zIqGDxsB4YR++CbQYNDpqwCoHDUJtxJ3rj7dCd5KRy1qU3xdAdNe18npDqkB1aIHqzVsymSk5P561//yh//+Ee2bLFOvY4YMYKUlM5ZU12INnMmkCBphUqkXVv3jzVxqk1a+MqpFNDQm6cc0Xs9D7gFOBtO7zf8H4/WtPnYKHvLt1MKcAbA42yxbW9ic3tQcZJMAJszfmIZi9PV8u1MrXC5PVZ7d2L3k2i77kYmcAnRu7R5SnBKSgqTJk1qz1iE6FC6xoH2K5QjTsJgaMz97jbt3yxJwjaoJn4MGoL7Utu0f+21gSsYMznVGnSt9eGs6+1ojw3ljpOcKo1ZlmTFXt7yY1YKzLI2HptKF7aM2KegtcYantsHqxTUFw8gecCuqMMJALSp8JTmtWnfVRWZ+P12HI7Yw0BstiClRf0B2F/cP6H9JtquO5EVuITofVo9nKC2tpbbbruNo446ipEjRzJ8+PCIHyG6Lb8N/5pcdIxOQa0Bv4F/fU6bdu/9cHDjfmLs3yxzQW3behoDa/rFP92vwLdsYMOdKXwr+8d/rFoRWG0tFa0r3QS2psdub4JZ4SK4vW1VPbxLhrTYxtp3q9+SerzS5bNiJrBgjYstWXZMm/bt97lY9cV0gsHox1Wb4PO6WPv1FAD27RrMnp2DMIPRn2hmULFn5yD27Rrcpni6ikzgEqJ3avV30iuvvJIPP/yQ73//++Tn56NaPmcpRLfhWzoYe2ElpHsjxotqE1DgeXM4+NtYYsvjxPfFAJwz9lmn3pu8NEI9jZ7/jmpz7N7FQ7GPKUOlNlY/CO1bKQgWu/F/nRtu7/tsIPYRFRg59c0eqzLA804Bur7xA93zTgEpl61Fu4LNj42p8Lw+nLaWVjL3phHYlIljdEX0Y+NX1L86ok377ulqdw6n6LM55B25JPy3gdCXIUXlhgmUrZ7e5v0vfv0Uho/dSHpmRbgqAYBpKhTw6nMX4vc11gFe9NxFzP/Zn7ERiGgfDBoEA3YWPXdRm2PpbLIClxC9W6vrxGZmZvL6669z9NFHd1RMHUbqxAoAleTHOWsXjomlKIf1IR3YkYbvk0EEt2e0cOuWOabvwTlzD0bDqXytwdzvxvPyKMz9B7mggmGSdN5GbAWNk7Z0EAIbsvEsGkGznkxXANfM3TgmF4fHswb3pOD9ZBDBLVnNdq8yPLhm7cI+rgxl09bwhy2ZeD8aHHeBhEQ5527HeWhReEiH1hDcm0L9i6Ohrm+NhY2k6Tf9YwbMeg9XtlVqzF+dTvHnc9j38fEHveBBcmo1c095i8kzvsDhtIYWbNs8nA/fPJltm5p/seo3YB9z5r3JuMmrMQyNaSo2rJrIB2/Mo3TfgIOKpbPIClxC9FyJ1oltdRJbWFjIG2+8wbhx4w46yM4mSayIYA9avZo+G7qu/T/kVHYdKtWPWZzU/pOVDNMqj2UqzD0ptHga3maiUn0QMNCJDGdwBlHJfrTH3iHjVI28WnAEMItTmi240LdpHBnlKGXiq8pqt9W6QuwOH2kZVXg9Lupq0lps70qqJzmlhrraVLz1Se0aS0eSCVxC9GyJJrGt/vS4++67+fWvf82TTz5JcnL7LdMpRKcL2NAV7ZskNKXLktFtq9bVMtPA3NWKL2JBA13ZiklZPhva13HHpj16dXsnhb8yu8P2HvA7KS/tl3B7b31Sj0peQSZwCdGXtPplfs8997Blyxby8vIoKCjA4Yj8pvvVV1+1W3BCCCFEopoOIZDxr0L0fq1OYs8666wOCEMIIYRoG5nAJUTf1Ook9vbbb++IOIQQrWDk1mEbVA2mIrAjHV0Rb6iAxjakGqNfPdpvENySGVGVQIho7O46Jh/7LmnZ5VSXZfHN4hMIeLrfELKoE7hMkxn+9QwOluBVDj5zTqDMdvCTNoUQ3YuMGhKiB1FpXtynb8E+tDpcj9YFBDZn4nl9RLNJWMaAGtynb8GW4wmXttJBhf+r/ng/GApm36vLKlo28/xnmXX0cpwGaK1RSnHiiUv46NPpfPzvS7s6vLDQ+NcJqY1fyqZ4N3Ka91NsaDRWUbhp/o3sU9n8M+VUAoZ87AnRW7T6EywYDPKnP/2JGTNmMGDAALKzsyN+hBAdxBUg+dJ1Vg8sVkIa+rGPqCD5wvVgNNb1NHLqSL5kPUaWJ9weQNk0julFuOdt7fSHILq/I899nuNmLcehrG9JoVrgDqU5buaXHHnu810ZXoTQAgYho/3bOcP7CQYNsTdsV8AAXcZPav/b2SEKITpQq5PYO++8k3vvvZcLL7yQyspKbrzxRs455xwMw+COO+7ogBCFEADOKcWodB8qStEAZYAtvw77mMZyCM6jd4PdjFi4INxegWNiKUZOXQdGLHoaZfdxzMxl4d7XiOuUQmvNMTOXoeyxlxDuDE9fvZc1D61oVgN2nudzIPqSHArI0dWM8O/snCCFEB2u1UnsM888w6OPPspNN92E3W7n4osv5rHHHuPXv/41n3/+eUfEKIQA7BNL4i6YpU0rMbUam9bqXnFe4ToI9vH72zdI0aMdcvRS3DZirsSolMJts9p1hUVjPax5aAVTxu/B7YhMYN2mhwxdF3dNOQ0c413V4XEKITpHq5PYffv2MXHiRABSU1OprKwE4LTTTuP1119v3+iEEGEqOUC8VZ6VASqlYUlaZzBqj+0Bt0Al+9stPtHzpWZVtGu79vT01XvDwwcmpDqaVSDIMGsTWhQ5CW/HBCiE6HStTmIHDx7M3r17ARgxYgTvvPMOAMuXL8flcsW7qRDiIOgqJ9qMc70JZoX1GtQeG9rfwke60ugqec2KRuVF/RNqV9bJS882ncAVaxWuciONRJafrFLdr8KCEKJtWp3Enn322bz//vsAXHfdddx2222MGjWKyy67jB/+8IftHqAQwuJf2T/ucAJlgH9VrnXBNPCvyUUH4+xQgX9N4qs3id5v47KjqPFbY1+j0VpT41ds+vyoTo3rwAlc0fgMJ6UqvcVEdrHr0HaLSwjRtVpda+T3v/99+PcLL7yQYcOG8emnnzJq1ChOP/30dg1OCNHIvyYXx+QSjLzaZmNdtQnB7zIJbskMb/N9OhD76DJICkQdG+v7dKD0xIpIpp13Xj+Js898s9nkrlBi+87rJ9GG/o82iVoDNo7/Js3iijprWFu0nHeHkccee2K9zUKI7k/pWF+5Y1i6dClHHXUUdntk/hsIBPj000855phj2jXA9lRVVUVGRga/uKACt6MV684L0V04A7iO24FjQinKZr10td/A/3V/vB8OgWBkcqEyvLhP3IpteGW4J8usteP7bBD+L/OI27Ur+qzxs9/jhNPeIsPV2JVf6bXx7msns/bD4zv8/kMrcEHrV+AaGtjLBXUfkIw3/Ow2gQ32YSx0zwFDaiML0d15qmr4fc5MKisrSU+Pna+1Oom12Wzs3buX/v0jv83u37+f/v37EwzGO3/ZtSSJFb2G248tzyqPFdybCr74s7hUuhcjux4CNoJ7UmSRA5EAk6GTVpKRW0xlSX92rJpCZ/TAtrb3NZbBgSIKgvvw4GSlY5QsciBED5JoEtvqV3W0+oFgJbEpKSmt3Z0Qoi08DoLbE19GU1e5CMrQAdEqBjtWde740dAErtb2vkazy57HLnteO0UmhOiOEk5izznnHMCqE/iDH/wgohJBMBhk1apVHHVU5w72F0II0XtUzi1HqYNPYIUQfUPCSWxGhtXro7UmLS2NpKSk8HVOp5MjjjiCH/3oR+0foRBCiF4tNIRg6kEOIRBC9C0JJ7GPP/44AAUFBdx8880ydEB0PEcQ24BaMDTBohTwtO+YNpXhxcj0oH02zH0poONNcjKxjarAyPZglrsJbsyks2ZoR+UKWMfGVAT3pYC/xZUNRFcwgqQM2o7h8OEpzcNfldXVEXUYZQQoPPRLktKqKd46nJJtI+K2tzt8bJ25hSHnbOEYsvA53F3aA5sTrCBD11Kr3BQZ2cSt6aU1+eZ+krSXciONciP+HAulgyT7SjB0gHpHNgFb+9aqTTXryDUrCGBjt60fZssrnQjRK7Q6K7j99tsjLn/44YfU1tZy5JFHkpXVe9+gRScyTJyzduGcVoRyWtX9dVDhX9MP7/tDwXdwyazKqsd94jbshVXhbWa1A+9Hgwmsal5+xzF9L67ZO1GOxjmQ2q/wfjQY/xcDDyqWVnMGcR273apOYG+oTuAz8H+Vh3fpYJmw1W1ocmd8RP6cN3CkVVtbNFRtHM+O1y7EV5HTxfG1r6PPf5ajjvySZHvja2RvlZtFT32fvd8eEtFWKZNjTnqHaSd9QJrNBxqCKNYGC3lTH4FHde7Y7cGBYk72fM4gs3EJ5hIjg3ddh7HJMaRZ+0P8Wzne8yVZuia8bbutP2+6j6TIlh3ZWGvyqr9hQPVK7Ka1UphGUZ5UwM6smQedzKaadczzfM7YwPbwV+o65eIT50Q+dU6In4gL0QskXJ3gD3/4AzU1Ndx9992ANaxg3rx54RW7+vfvz/vvv8/48eM7LtqDJNUJegKN++xN2EeXN3v/1SaYxcnUPX0IBNrW06AyPaRcvgZcwYjaqVpb7/eexUPxf5Ef3u6YsQfX3J3WbVVkewDv0sH4PxvUplhazWaSfOk6jAHR68QGtmTieWk0Ujar6+XPfZ2Bx77RbLsOGgTqU1j/t//tNb2yx//gMY4+dG2zSb+m1gS04vGHrmLf5rENWzVnXvosk2d82ez1HURRZqTzWMpp+JSzU2IfHCjm8ro3MdAYTZZJMLFeRQuT5rLeURDePsW3kTM9n6CJfJWZKALY+EfKqRQ3SWQHl39CXs2aZverUfhsKazPO4egLanZ9YlINj38qPZV0nQdtihLPHzuPIS33Ye3ad9CdLVEqxMk3G3zwgsvMGHChPDlF198kaVLl/LRRx9RWlrK9OnTufPOOw8uatHn2QoqcYxpnsCCtSKVkVeHY1JJm/fvOmZnswQWGhNU1+ydqCR/w1YT1+xdEdc3az9zF9ZHXsdzTCzByG+ewIJ1bByjKrANr+yUWERsjvRy8ue8GfU6ZTOxJ9XGvL6nSc0p5oipVpJ2YNUaQynsSnPSxc+Ftw0u2M6Uw5snsAA2NDlmFYf5NnRozE3N83zeLIGFxg/GUzyfoRrWenZoPyd7ljVLYK32GjtBTvQsD29z+8ujJrAACo0zWEte9ao2x36UbzXpMRJYgCN86+gXrGjz/oXoCRJOYrdu3cqkSZPCl9944w3OO+88jj76aLKzs/nVr37FZ5991iFBir7DMbkE3UJO6JhS3LaduwLYx5ZFTQLDlMZ+iHVa0T6pBGXTMc/IKQXKBo6pbYynlRxTiom3pqY2wTG5c2IRseVMWRb3emUzyZmyDGXzx23XExw27/W4HyKGUgztV0lypvWaSp3/AcE4ZwoUmmm+b9s5yuhyg+UMNPc3S2AbY4FU7WFkYDcAYwM7cBKIGb2BZkRwD2lmLQA5tRvQLTzW3Jr1jad1WkNrDvVtjBk7WD3bU/ybWr9vIXqQhJPYQCAQUVbrs88+iyipNXDgQEpLS9s3OtHnGBneuEmmUmCk+9q0b5Xsj5/AAmiFkW6NXbPl1ie0XyPBdgdLpfviHxsDjExvp8QiYnNmlKPjThIEwxHAnlzbSRF1nIzs8njfqwArkd04fQdrHlrB2KzimD2HYCWO6bpzjkuG2fL9aCCjIZ4MswYzgaE6of06AzUttAS79qJo/QJBdoIkEf99UJHYYxSiJ0s4iR0xYgRLly4FYMeOHWzcuDFiidldu3aRk9O7JiuIzqfrHHF7YrUGXd/GiV0ee8udHkqj66wZ0mZ1YuPyEm13sHR9/Pi1CbpWyhN1tUBdaoupjjYNgp62jYXsTupqUhIage08Y7915sKe3GIiWN9JE7vqjJbvRwG1ym21V+64PZ8htYbVPmBzt9g6qGxoWj++P4ANfwu301gxC9GbJZzEXnPNNVx77bVcccUVzJs3jyOPPJJDDmmcdbp48WKmTp3aIUGKvsO/pl/83lIN/lW5bdq3rncQ3JoRf7iCAv9668uY/8sBVmIY45NIaytx9C/vnFWBAqty4w4nUIZ1/ETXKlt1GMoW+0mmgwbl6yZj+nv+CmpfvntS3OtNrdnmdVHlymJ8ioPVjhFxE0ETxUrHqPYOM6o9Rj/KVFrcRNODg032wQCstw8jGOcj0wR2GznhcltlyaPiPlaNoix5TNsqCCjFKseIuEMzbGhWOeKXOROip0s4if3Rj37Egw8+SFlZGccccwwvvfRSxPV79uzhhz/8YbsHKPqWwMYsgntToiaaOgi6xoHv6+ZlsBJllaFS0fevwb8iDx1antU08H+Ti1LRE1mlGpLGQOesye5b2R9d7URHOfuoTQjuSyawIbv5laJTeUoGUPrVEWizeYKhTYU2bexdMq8LImt/ZTsLWLttINGK3IS2veCYHN622T6IbbYBUXtjgyjqlYtlzkOaXdchlOJd92EoYn83XOKaSkBZr+96w83HzklR21m3V7zvnh7eVuvMo8I9LOq4WI0iqBzsS5/c7LpEfeKaiB971GNpAhvsQ9ltky+1ondLuMRWbyAltnoIVwD3qVtwjK4IJ49KQWB3Kp5XR6IrD64Hyza0Evep32Fk+MKltXRA4ftyAL4PhzRb9MB1yhYcE0vDyWzo/8DaHDyvjTyoWFpLpXtxn7EZ++CayGOzOZP614aDR4YTdAtGkMEnv0T/GR+hbGZjCbf9/dj20uXU7hze1RG2G2UEOOOaPzNp5HYMpcKltmpNeJwp7M+MPEPn1H5Or/+Y8YFtjfsA9hjZvJQ0hzJbRqfGP8H/HfM8n5OsveHKA17sfOA61EqoD6itN8v3DbO8q3AQDLevVkm85j6KjY6hEftWZoCh5R+RU7eJxlQX6u1ZbM05jnrnwQ3BywuWcW79EnLNynAirlGsdIzkDfcRBFXnfMEWor0lWmIroSS2tra2VSt0tbZ9Z5EktmdRmR7sw6qsFbv2pGIWtedzSmMrqMTItlbsCmzOjJ8AOgM4j96NkeHFrHTh+2xQu68g1hpG/1psg2pAQ2B7Brpcxr51R/aUajJGr8FwevEU51O9bRTo3rkgRUp2CZOPfZ+iCWVUZSSzzD2O4Umxx/1mmDWMCOzGhsluWz/2GP26rDi/oYOMCuwKr9i10T4Ev4r9fuDUPsYEdlordqk0NtsHoeOMg3IEakn37MTQAeqc/ah15rXfY9WaIcFiBphlBLCxyT6YGqN9VwQTorO1axKbn5/Pz372My6//HLy8/OjttFa895773HvvfdyzDHHcMstt7Q9+g4iSawQQnSsp6/eyxFT9nTpErJCiJ4t0SQ2oa6kJUuW8Mtf/pI77riDyZMnM336dAYOHIjb7aa8vJx169bx2WefYbfbueWWW7jqqqva7YEIIYTo/haN9VB47VqmdHUgQog+I6EkdsyYMbz00kvs2LGDhQsX8tFHH/Hpp59SX19Pv379mDp1Ko8++ijz5s3DZmvbcqBCCCF6pqev3suU8XtwO5AeWCFEp5GJXaLvspmoVD/4DHR9B3zwuv0oVxBd64RAS+MgTWvRBIeJuS8FzN45blL0LqHkVSkYn+IgyfTgwk+NSgrP6u8qjmA9/Xx7qDdSqHANaPf9Zwf2kxmoYK+9P/X2tHbfvxB9WbsOJxCiN1FJfpwzd+OYWIJyWrW2AtvT8H0yiOCOg58ZbRtShXPmLuzDqgHQfgP/6n74Ph4cXkihKdcJW3FMKkE5rO+TWkNwZxr1L44Gn7xERfe0aKwn3Pt6nK2UObUrKQjuA8CPjZWOUSxxTaXO6NxJh2n+Uk6teovhdh+OhslTZbWaz23DWZ4x56D3f3jtcuYE1uLCRCmF9moqcfCSeza7XENb3oEQot1Id4/oU1SSn+TL1uKYWhROYAFsQ6pJungD9jH7D2r/9tFlJF28HtuQ6sb7dJg4phSTfNkaVLI/on3SRetxTisGe+MJEaWseFKuXgn2wEHFI0RHqZxbjtsBpxu7uazuLYYGi8LXOQgyzf8tV9YuItn0dFpMKf4yrqx5lVFNEliALBvM4zuOK1t0UPs/rmYpJwVWhxNYAKUUGfj5oed9hnq3H9T+hRCtI0ms6FOcs3ahMrzNVgULXXaf+h04Wr+WOQD2oHV7RdT9q3QfzmN2hrfZCsuxF1RZ1x9QbUcpUO4g7lO3ti0WITrIorEe1jy0ginj9+DUAc6s/xgFzVanMtCk61qO9a7otNhOrXqTVAOMA15QoYTzSFsJ6b6SNu3bHvRydHBLxP4i96+5oH5Jm/YthGgbSWJF32EPWkMIYjzrlQIcJo5xbeuNtY8tA2cwZvlHZYBjQik4rSTZNXtXzCVtw/scVd6mWIToCE9fvZfCa9fidsCEVAenG7tw4o+5+KkNzST/FhzaH6NF+1FBHyNt3mYJbPh6pTCAmTVL27T/E+s+sr5cxtl/sgqS59/Xpv0LIVpPBtyJPkOl+cPjTmMyFUZO205/GtkeMBXYYt+HsmuMNC/m/mRUmi9uvXOlQMfZlxCdJTSBa2rDBK6QfmYlJgY2oqzj3MBBkHSzlv22zA6NMTtQgsOIv4CABrJ1XZv2P0BXhFcji0UpRYFvJ0WO9p9IJoRork1JbEVFBV988QXFxcWYZuSb12WXXdYugQnR7nwJnHhQGp1Iu2j8BqiWk07tbyhDFzTCy5EK0V01ncB1YPksn7KjaPk574uz+lV7qU9wlSp/G09AehP8uKyV1bKE6DStTmIXLVrEpZdeSk1NDenp6RHfSpVSksSKbkvXOgnuScEYUBt7SIEBgW+z27R//7fZuGbvin3/JpjFyegqFwCBDVk4ZxTFbq/B3C/LyYquVTm3HKWi139dby/gWO/XMW9rAnuNHKqNjl+GvM6RRXE19LPpmEMKDKVY5RzVpv1/5JrKCM/7Ma/XWqNRrHGObdP+hRCt1+qvpDfddBM//OEPqampoaKigvLy8vBPWVlZR8QY4S9/+QsFBQW43W4OP/xwvvjiiw6/T9F7eD8eDIqoY1G1Cf5vszBL29aTosuS8K/PRkc5s6q1lSB7Px7cGMvSweiAih5Lwzbv+1KyR3SNphO4XDG6O0ptmayzD8OMMipWY33AfOia2qFxNvWJfQwKK6E8kKk1xQFYnzytTfve4RpGFY6o+warE2e1ygdZ8EeITtPqJHb37t1cf/31JCd3/imTF154gRtvvJHbb7+dr776ismTJ3PSSSdRXFzc6bGInin4XSae14dD0EoedVChG4oRBDZn4XltxEHt3/P6cAIbswDQwYb9ayCoqH+jkODmrMbGATt1T42HgJUAaB2ZXHvfG0pwa5P2QnSSAydwxVuF6+WkY9hgt75sBVEEGuoUBLDxinsmmxxDOilqWJV+FO+bgwhiJbJmww9ASUDxr7QzDyrJ/EvqedQ0nMDUWkf8bCGL/6af3B4PQwiRoFav2HXOOedw0UUXccEFF3RUTDEdfvjhHHbYYTz00EMAmKbJkCFDuO666/jFL37R4u1lxS4R5grgOGQ/RrYH7bMR2JCNWdJ+X8yMfnXYx5WhnEHMchf+tf3AG2v0joljWhH28ftRhia4OxXvh0NkoQPR6RaN9VB47drwClyt0T9YxiH+bbjws99IZ7VjOF7l6qBI40v2V3B09Yf009X4sbHaNYZvUw9tt/2Prd/ATN8q3PipVMm8mXQ0pY7+7bZ/Ifq6RFfsSiiJffXVV8O/l5SUcNdddzF//nwmTpyIwxH5RnfGGWccRNix+Xw+kpOTefHFFznrrLPC2y+//HIqKip45ZVXmt3G6/Xi9XrDl6uqqhgyZIgksUII0cTTV+/lumkfM3vnBhQw8sPVXR2SEKIP+2baKI46dEH7LDvbNGkMueuuu5ptU0oRDLaxUHwLSktLCQaD5OXlRWzPy8tjw4YNUW+zYMEC7rzzzg6JRwgheoOsxxay4fRbAcIjWw2j46sJCCFELOOfW5VQu4SS2APLaPUUt9xyCzfeeGP4cqgnVggh+qpFY606yJVzy9lwx2w43UpejdzhXRuYEEKE+APAxhabtXpi17/+9a+IU/QhPp+Pf/3rX63dXcL69euHzWajqCiyJFFRUREDBkQvLO1yuUhPT4/4EUKIvmjRWA9n3X43yz6cxLIPJ1kJLGDLHS4JrBCiR2r1xC6bzcbevXvp3z9yEPv+/fvp379/hw0nAGti14wZM/jzn/8MWD3EQ4cO5dprr5WJXd2ckVOHY8ZeHOPKwG5ilrnxrxiA/5tcMJt/l7INrcJx2F7shZWgILg3Bf/yfALfZkHMRS67B2NYJe7jt2P0q7c2mBDYkonnjRHgaX7ywxhYjXPGXuwjKsDQmEUp+L4cQGBdDs0fq8Y+uhzH9H3YBtWAhuC2dHzL8wluz+joh3bQkvJ3kHf0+2SOW4VhD1BflE/x53PY//URoA9yFWwjwLAznidr4pcYDmuZU19FFnveO4OyVTOaN3d4yT18KbmHfYQzs4yg103ZyhkUfXocvoqcg4sFGHzIKo454xUKB5RhKE21z8bKbyay9PlLMAPOZu0LRm3iyLlLGD5mI8ow2bVtGJ9/MIcNqybS/HlgcvjZLzH98OVkJ/nQwK6ydD556yQ2LTu62b7XPLSC58+/GACb4YCcLj4jdWYuzM4GR8Pj0sC3tfCXnc2aamDfISl8d3QGFUPcKK3pt7me4R9X0G9r89X1TDuUX5yPe0oaSU4DU0NlkRfXf0tIXVvTPJYkw4rl6EzIsENdED6vhA/KoDLQrg87IYekwLHZMDIF0LC5DhaXwbra5m0VcHiGFf9AFwQ0rKqG98tgV9tWHuxUo5Ph2BwYkwyGgq11sLjcegzRTE+HOdkwxA1BDWtrrGOztb5z4xYdrsofIOPFxe0zsaspwzAoKioiNzc3Yvs333zD3LlzO7RW7AsvvMDll1/OI488wowZM7j//vv597//zYYNG5qNlY1GktiuYRtWSdL534LSqIbqNqFnXXBbOvUvjoFgYwLjmFqE+6Rt6CCN7U2rzqrvizy8i4fRXRNZ+6Qi3PO2AY0rcYVfYT6DmocnQ31jAmMfX4L7tO/AjPJYV/XD+8Zwmj5W15wdOI/YG27TtL3nvWH4v+y+y11mjlvJ8Av/YdUPtVlDlLSpQGkq1k3huxeuaHsiawSY8PPbcWZUAM2PfdHHx7H7nXMam7vqGXPFfSTl7bGel6H2QYOg38nGf9xA/b62J3rj577L2We9bp2mV6ESalYwe6uS+efdvyboa1zIYsYxS5l33ssEgwa2hmNjmgrD0Hz6/hzefeUMGp8HJhf97+8YM2g/pm4s7G9qjQLe/3gGv1h9DpfdvAiA2Ts3MOGnT3WfIQPXD4VRDZVAmv6hlLISyP/XeApRA+tOzmHrrEwwtZXoACqo0TbF+EUlFH5eFW5vOqHq9pFkpNsbdt94bDRQ/Z8iMj8ob4wl1QY3FkA/R3jfgJUg1QXhvu1Q7GvnAxDHyf3gtFzr/m2qMRabgkXF8Pb+xrYK+OEgmJLWUJS3SXuAf+yOnQx2B3Oy4LwB0R/ru/vhlQNKZ16aD0dmRjwPCGrrODy9F76o7MzoRQdLNIlN+BNj6tSpHHrooSilOO644zj00EPDP5MnT2bWrFkcf/zx7RJ8LBdeeCF/+tOf+PWvf82UKVNYuXIlb731VkIJrOgi9iBJZ28CozGBBevzSimwDavCefje8HYjpx7XidusNk3bNzxTnTOKsI2o6Pi428IwcZ+8DYhcSjb0WHGaJJ/f+AGt0ry4T/nO+j3aY51Uiv2Qxg8tW0EFziP2RrRp+rvV+9u2deE7mi2phsLzHwdlhhNYAGVYCWTmISvJPezjNu+/4OyncGZUNB7r0P4bfs+b+T7OnMahSINP/C9JeXvD9x9ubzOxOXwMv+gxUG2bC+BKqebMM9/AgIiVo5RSKKXIT6/jhMv/Gd7eb8A+Tj73ZYBwAgtgGFYyctRxSxg5rnHy6owz/8OYQdbzoun+Q78fO/MLPtw1i2tOv5VrT7+ViT99Cpvh6B4J7MSU5gls09+TbfDTxi8PJaOTrQQWIpJM3ZD0rD2tH9W5jZPQyn8wiIx0e/hYhxhKYQApZ+cRSGny4rlgAOQckMCClUgl2+DygW1+qK1WmGQlsKH7bxoLwOn9oaDJCn5HZ1oJrFKR8duUldjNHwgp3XThhXyXlcBC9Md6Qg6Ma7LK2/R0K4GF6I/10nzIlJKEfVHCSexZZ53FmWeeidaak046iTPPPDP8c9FFF/HII4/w9NNPd2SsAFx77bVs374dr9fLsmXLOPzwwzv8PkXb2ceVgSsYc5lXFDgOLQJlfWA7phYRbyl2bYJzWuylWruS85hdKCPys7kppcDIrwWndYrSMbkEVOz22gTn9H3hy45pReGFGaK2DzYcv24oZ+oylC3O8wDIPeKDNu8/a0LspU9Dx3fIyf8BrF7YnKmfo4zoSaqymbhzSkkrbHlSQTSHnfYqdqUjkqgDTTpkExjW8+Cwoz/BjDKkJiQYNJhxzEeN+z/ii3AB/2axN9xn/cVjw2NdjdzhXT98IOSCfOv/mE96DWMbk5etR6Q39ixGoUzYfrg1jEYbkDo+NXZbpbArqDy9IVFMt1tJoC1GLDYFw5KsU9ed4ZisuI+VoLbahMyNszy2oaz4D++mQ4xmZbbusc7Jtnpgo1ENiexRme0YoOgpEv7qcvvttwNQUFDAhRdeiNsta7qLltkG1IKpwBbrQxdUqh+V4kfXODHya+ImOsoAW36UcW3dgG1wdfisaCxKgW1INcEtWdgG1MQdFaEMMPIae1ZtA2siemybtbdhjZPthpIH7oh7vVKQlFuMsvvQUcaLxmM4PRj2lsfiJw3YDYC7XxGGI/5YRx00SB60g+rvxrYqFoCBQ3egif2nVUqRZIOM/vuo3DeYQQXbI3pgD2SzmQwq2B6+nJXsi+iBPZChFPahGUBJq2PvcGm2ll8gTb7FVgx2x04ysXpky4dYCyr4cp24bPH7ZTRYiSnAIFfzHthmN9Aw1A07O2F8aWFS3MeKTUFhQy+2XUFeAgtJDO2mn9MFCTzWgqTGy0Pc8f9Wisa/q+hTWt3/fvnll3dEHKK3CkZ+KMVvBwSNFhNBbXbP8bDhx9AC7bc+aLVpEDfbAesLQLTfo+1XW8lXd6SDdtDxnwtagzZbf/rTDNhbfM5YDRuOezCB+1A6sXZRBBO8XcBnJSGBBOIPBhr3qbWK+5zRWqPj9XJ1JQ2J/bEsRkuPQ2uMgNVG+RIb/hE+NoEEjpFS8XsM21Mi8YTamLrl46gT3GdXCCQQf9PYm46bjaY7P1bRoRL6xMvKyiI7OzuhHyGaCmzJjNt7qE0I7k1G11vj2gKbs2I3xjplHtjYPZ9n/lW58T9TtBW/uSMNgOCWzPjJSBACmzPDlwMbs+IOJ0BDcFP849dVKjeOR8XpbdRBg6rNY6ENSSymnUBdCvGmqCoFFRsmAlBfPBB/dXr89oamcuP41scCfPv11Lg9pabW7K+zU1tmndbeuGa8lZjGEAwafLvain3RWA+lAWIOJwjfx4YoM9m7g13NyzNG0BqaJKMD1tei4iWRGvI2WGcrnOUBqusCcY+NoRT2rxomgm2rh/oWevBNDes76Viuqm75FHtoopYJbKiN396mrNn73dHqmvh9G00fK8DqFo6NAtZ008cqOlRCSez999/Pfffdx3333cevfvUrAE466STuuOMO7rjjDk466SQAbrvtto6LVPRIwe3pBIuS0DHyF2WA7/PGyRP+Vf3Aa4va3vpsUvhXdM+JfIG1uZgeI2ZypBQE1vYj9LLzr8tB1zpiP1YFvi/yw9v8KwYAKur+tQn4bVbJsm6oYv1kvOU5MXuKlc2k6OMT2rz/fUtPjDvMUgcN9rx/urXBtLHvoxPijEU2qPh2PN7StlV6WPPhXCq8tpjJlKEUn300M3z5688Px+d1YUbpadcatA2emZXNmodWsOzDSbgf/hpFY7WDpkyt8ZmQ8Wpxs+u6hccbSmhFfRI3bHuvcTJjwWcNM86jjYc0NXafydAVjdUJAkvLY36BMLWmxhskY0lDdQK/tspoxXrBmhqWV3Zema2Pyq1ELcZjJaitNiHv7Y/dOxnUUOqDb7ppdYLPKsBrxn6sGlja5LEuLqPhSd+8fVBDdRBWSHWCvqjVJbbOPfdc5s6dy7XXXhux/aGHHuK9997jv//9b3vG166kxFbXUGleki7agC3HEy4HpU2sJG3JEHzLImcAGwNqSL5wA7iDjafbNWAqPK+MJLCpe/bEAqjsOlLmr0E5dPhsWej/wK5U6p8eR9PvjkZuHUkXbkCl+CMfqwbP6yMIrOsXsX/biPJwtYeIXlyvjbp/j8Hck9YJj7JtXNnFjJr/IK7M8nBpLRp6IHe8diGly2cd1P4Lzn2C7MnLI7YpZQ0/2fTkNVR/N67JNZrBp7xI3pFL0EEDZTPD/9fsKGDzU9cQ9CS3OZbsIdv4wc/+TJrTDJe+Cv15P/9mHO/886qI9oOGbefSqx/BnVQffr6YWqGURv9xOaywklKFVSar7Oz+ZB6b3awj32eC/7FdpK7uxr1Sc7PhnP7Rr1tfC3+NrBVbNDaZFRflYYZmojccSIfHZMYTe8k6oHd3/5WDyJ6cFvFyMpSizmdi3L8N944m7RXwvXw4PLPxlHXo//U18Ogu8HXiaerRyXDVEKt+buiPq7ES7od3wqYDqo8cnQkXDmh4kDSW2irzwYM7oNTfebG3VoEbfjrUqtPb9I8V1FZ5sAN7Vqenw/cHWu2avqCqg/DQDtjTQi+/6FE6rE5samoqK1euZOTIkRHbN2/ezJQpU6ip6b5vnpLEdiHDxD66HPuYMpQjiLk/Gd/K/ujyGBMPnAEcE0qxFVShDE1wdyr+b/qj63rAmu6GiXPWLhyH7Ae7ia524v14EMHNMZJvRxDHuP3YRlSgbCbBfan4V/ZH10Sf4KSS/Dgml2AbZE0kC27PwL+mH3i7f4kZZfeTNf4rMsetQtn91O8bTOmXR7fL4gIAKUO2MOik/+LOKUYHbVRuHM+ud87E9ESftZ40YCf9pn2KK7uUQH0KZaumU7XpkINfeAGwOT1MO/l1xk1ZhcMeYP/+bD59/VSKNkefLOZ0e5h82HKGj9lIzaRyDn3uffTindhqdNTqAp6BTmrO6o8934U2rSEEGa8WY6/tAcuEZ9lg/mAY7LYSkcoAPL8XNkQvEedNsbFzWhplw9woE/ptqWPw19U4vNE/vmpHJVN/aj9s/ZxovwnfVJP5RglGrJKvw9xWCacsB1QHrJqjG7uoXF2yAUdkwsiGL1Gb6+DzCqiL8XfNdljJ7CCXleyuroGvqnrGGFG3YVVQGJ1iJeHf1Vu9tDUxhnlk2K0qBMPc1uNbW2v1wHbmFw3RKTosiR02bBjXX389N910U8T2e+65hwcffJDt27fHuGXXkyRWCNEdPX31Xr5Z/zNcL6wMbwv1ugohRF+TaBLb6q6bO++8kyuvvJIlS5aEa7QuW7aMt956i0cffbTtEQshRB+U9dhCNpx+KwA2SVqFECJhrU5if/CDHzBu3DgefPBB/vMfq3j4uHHj+Pjjj2XhASGEaMHTV+/lumnW6mRXPr0Q1+krpddVCCHaoE2D6A4//HCeeeaZ9o5FCCF6tbNuv5tf/fQpoHHejiSvQgjRNgklsVVVVeExCVVVVXHbxhu7IESiVIYH57QibMMrwNAEd6bj/yoPsyilxduKvit12GZyZywledB2dMBB+boplC6fib86s3ljZZI5bhX9pn+MO6eYQF0K+7+Zwf6vj8D0tu/qP2seWsHz518MP4091rU22862wzMoGZ2MNiB7q4eCZZVk7I0+G6l8sIttR2RQPtSFEYC8DbUULKsiKUpJKA0Uj0lm+2HpVOc5cdQHGbSqhiFfVuP0RJkwZFcwrWG9+kw7VASsCTcrok8Y8rkNdk5PY/ekVPxJNtKKfQz7oor+39bFXcsjUVUDnGw9IoOyQmtiV+7GOgqWVZJS1knlr3oLBUxOsyaC5TqtCVTLK+HzSqvklRA9TEITu2w2G3v37qV///4YhhF1TXCtrbXCg8GWl3/sKjKxq2ewjWwoI6V0eAlaHQQM8L47DP9XbavfKXozzcDjXyV/9jvhUllgldcy/U42PXkttTsbE0dlCzD8okfJHLumscRWwzuhryKHbx/7Of6qg184YtFYD/+48I9M+OlTcYcM7BuXzIqLBoCyllIFUEGNNmDColIKlkV2HmyelcmGk3OsNqFaoabGCGoOe2ofuVvqG4+Mgq/P78+eyWmN7bVVi9NVE+TIx/aQur9JKSa3AdcNtZbxNLVVsin0//Z6+PMOaJL41uQ4+OzKgXhTbQ3lj1T4fgZ+U83UhcWog5g8vm1GOmvO6IcyI48NGqY9v48B67uoikBPYwN+NBgmpDWWEQs96ff74f7t1pcVIbqBdp3YtXjx4vBqXIsXL46axArRHlSal6SzrDqoTZ9moVW/3CduJ1iUgrm7+9ZDFZ0vc/zX5M9+ByBiZTBlaAyHj5Hf/xur/3Q3ps8q6ZY/500yRq+NaB96vjnTyxlx8aNseOR/iL8mcHRrHlrBky/+AYBfvbASPgSb4YhaJgugPsPOiosGoG1NgqAxYVtzRi4Ze7xk7bTqYJaMSGLDyTkRbQAwFCbw5fcGcNwft+NsKMn03dGZ7JmUGtleWXVIfSk2ln9/AHMe2NmYaF40wCp91bDPiP8Hu63rn9hj7U/B8u8PwJdii1jbPnQ/eyalkrHHx4iPKxI9fBHKh7hYc2Zuwz4bt4cS8RUXDeDYe3dE7X0WBzg1Fw5pKDXX9HkAVmmxKwbBPd23upAQ0SSUxM6ePZutW7dSWFjInDlzOjgk0Zc5phQ3S2Cb0kFwTt+HR5JY0UTe0e+jTYUymnf5KUNjc9eRPelLSr+cibL7yT1iSdS2YCW1KYO3kzxoO3W7CxKOIVwm6/yGiVqGA+IkryHbZ6RbZWljPOlVULP1yAyydloLHnw3MzP2WvKGImiHnYemM+LjCrSC747OiHnf2qaozXVSOjzJ6r3NsMOh6REJaQSbsq5/uRgqA5QOT6I2N3o945Dvjs6g8NMKjDacrd56ZEZkb3NTSqENzfYZ6Yx9t6z1O+9LHApmZcX/uxYmw1A37PB0bmxCHISEJ3aNGDGCYcOGMXfuXI499ljmzJnD4MGDOzI20QfZhlWFhxBEo2xWGyHCjCCpQ7bFb6MVqQWbKP1yJkn992J3x/+g1qYirWBTi0nsmodWADDL/V2by2SVDk+KnVxgJZqlIxrH6O4vcMdebhRAQelwNyM+hrosO970+G/zKqjZH0piC+PHAljXFybBymr2FybFTjIBlMKbbqc+096m8aulI5Ji77shltLh7Tt+uVfKd0GSLX4bU1sLLEgSK3qQhJPYxYsXs2TJEpYsWcJzzz2Hz+dj+PDhHHvsscydO5e5c+eSl9c917QXQohGB7+6T9Ne15BOK5PVkaO5WrtvGVnWM8jfSfRSCSexc+bMCQ8l8Hg8fPrpp+Gk9sknn8Tv9zN27FjWrl3bUbGKPiC4PR3bwJqYvbE6aLURIsy0UbOzgJRB22MOEUBparZZS2XXF+cT8Ljj9sYqQ1O9fWTU65qWyWqPxQn6fVdPxWBXzB5QFdT0+65xolbOVk/8HkpttQFILg/gqgrgTbPFHK6gbYqcrQ37/66+cRJXLKaGhvY5W+vZPCfOBDitcVUHSWrjhKF+W+rZOyE19mM1I4+NiGGPF+qD8XtjDWUtcStED9KmBcLdbjfHHnssv/rVr7jzzju5/vrrSU1NZcOGDe0dn+hj/Cv7g6mIVTND2cD/pVQnEJGKPjkuZgKrTUXQk0TZqsOsywEnJctmo80YSV3QoHbXUOp2FQDWkIH/mXMB/zPnAn5VNDpcaaC9Vtca9kUVysRKDqPFY1MUfloZvjz8k4q4SZ0R0AxdYQ25UZqI2x5IBTUpJT76haoZVAbgqyprzG00QW1d3zCRqt+WelJKfFa1gBgKP61s03hYgMLPKuM+VmVax0+0wK/ho/KYzzGCGrbVy1AC0eO0Kon1+XwsXbqUO++8k7lz55KZmclPfvITysvLeeihh9i6dWtHxSn6CF3tov6/o6xEtskHn26o3OZ5dxhBmdQlDlCxdir7lp4AWEloSKjE1uanfhquTACw94NTqNx0SLgNNFSd0uCrymTL8z9i0VgvZ91+N8+ffzHuF1aSvHAtNsOBLXd4uw4bSKoMMO35fShNRDJolZHSjF9UEq5MAJC7uZ6xb+9vbBNqHyqx9fS+cGUCgBEfV5C/uiayvdZgapx1QQ57el9kCawX9sFuT7gNYP2vtbX9hX2N96nhsKf24awLNrZpcj/5q2vaXJkAIGunlwmvloDWzY6NaiixJZUJEvRGKayvtX5v+jzQGsr98NiurotNiDZKqE4swLHHHsuyZcsoLCxk9uzZzJo1i9mzZ5Ofn9/RMbYbqRPbc6jMxsUOlKEJ7kzDt2KALHYg4kot2ETujKWkDNqO6XdQsX4KJV/Mir3YwSEr6Tf9k/BiB2UrD6f06yNYdc86a3EC4pfHak81OQ62H55O8ehktKHI3lpP4bJKMvbEWOxgiLXYQdlQN7aAJm9DLcOWVZEc5dS9VlA0JpntM9KpyXXi8JgM+qaGISuqcNbHWOxgepTFDr6MsdhBksHOaensnpyK322QWmItdpD3bd1B1YgNqRzoZOvhGZQVJqFMTf+NdQxbVhVZ31a0TAFTmix2UBuEZZXWT7RFL4ToIonWiU04iXU4HOTn53PWWWcxZ84cZs+eTU5OTrsF3BkkiRVCRLNorIfKueUA1oStF1Z23kQtIYQQEdp1sQOAiooKPvroI5YsWcIf/vAHLr74YkaPHs3s2bPDSW1ubm67BC+EEJ0l67GFLDv9VviwcVt7jXcVQgjRcRLuiT1QdXU1H3/8MR988AFLlizhm2++YdSoUaxZs6a9Y2w30hMrhAgJl8mSXlchhOhW2r0n9kApKSlkZ2eTnZ1NVlYWdrud9evXt3V3QgjR4bIeW8jsnVYVlfYskyWEEKLzJZzEmqbJl19+yZIlS/jggw/45JNPqK2tZdCgQcydO5e//OUvzJ07tyNjFUKIuNIzyzn0yM/JG7ybYMDOxjXjWfv1FL65f5U1Uev0xrrvhuFgz6yxbJqbhTfdhs2nGfJVNSM/LI9dEmpUMszIgFQblAfg84ouK0tUOcDJ+nk5VOU5MUzot7mOQ97aH1GZIEKeE47KhP5OqDfh6ypYWwOxHuvwJDg8A9LtUBWwJv/EqslqB07uB9MzwGlYs91fL4F1tVGbBx2K3ZNSKRmVjGlXZO7yMGRFNe7qYGsPQ7uoGORi57Q06jPsuGqDDPq6mpytHlkjAGB0MhzWPZ7zZNityYZD3dYEw3U1sKLKKiEm+qSEhxOkp6dTW1vLgAEDwit0zZkzhxEjRnR0jO1GhhMI0XtNPfJzTrvg36BAKY2JwqY0vqDC9vPFqKK68JABE/j4p4OoGuS2SgwpFf7f5gky+4GdJFc1SagcCq4cDONTrfJENtX4/2cV8Oze9lgILGFrTslh21EZza/QMO25IvIPTB5P6Qen5FoxG1gHwKZglwce2gE1TR6rDfjBIJia3vyxfl0FT+yGprlmnhP+t9BKXpt+nCgFm2rhgR0RoVT1d/L5D/PxpdqsY6asuJWGqQuLGLg6euLbEbSCb87OZde09PDyuaH/czfWMf3Zfdj6aoLkUPDjwTAuynP+0wp4rnOf80xLh8sGWs+XhucMCusL1p93wL7oVTxEz5TocIKE68T+8Y9/ZP369ezevZunn36aK664okclsEKI3qtg1CZOv+gFlKExDI1SYGuo7eQgiO1Xh2MMaBw2sOKSPCuBhcaVrBr+D7oMPv7p4Mg7uHAAjGso7xYqvh/6/4gMmNevQx5XNDunpDYmsEod8AMrLs7Dk9Lkrf3wDCuBDcVsHRzrcr4LfnTAYz0rDyanNbZv+v/kNOv6pm4usBKeA+MBGJUCFzcuThJwKj6/Ih9fcsMKYoYK/68N+OqCPCoGudp+cFpp49wsdh1qPdbQogqh/0tGJrHqjM77u3Y7Fw2AMTGe80dmwEmdeGyGueHygVbG0uQ5g1KQaofrh4FT+s37ooST2KuuuorRo0d3ZCxCCNEmRx23mKBWUVdWVTYD+ieHE7OAHYrGpRB7WTiFL81O0agk63KG3RpCEGspVqVgbnZjItfBvj0+u/F+o8WiYP28JuUPT8qJ/VhtCkYkW0kCQJIBMzNjP1ZDWdcnNXx0HJ5uLWUaY0lbtLaS6Aa7J6fhS7E1JkMHxK40fHd0lB7mDhC0K7YenRk7dkOxe0oanrQ4S7X2Vpl2awhBvOf8cZ33nOfY7Iae1yj3Z1OQZoNpnfO8Ed1Lm5adFUKI7iDrsYX8z5wLGDluPfYYy84C1mnQ8alAQwJrqNjJC4DW7JjRcAprbErsD/OQJBsUJLUy+rbxZNrjxw6UjEy2fslxQH9X/PZNjg2jUsDRwseCw7DGBgMckRk7QQbrfu2GNb4WKB6THPcUtLYpisZ2zoIm5UNcBNwtPFZDNR7LviTR5/ywznnOMzEt+hefEA2Ml4Vw+qI2VycQQoiuEi6PdfpKlE2hzhkU/wYKaxUqrElFiTAb2mNvHC8bl72TeqVaohQ6lIDE++AP0box9kQ/Eeyt2D+Ay0oWTZtqMTkyE93nQUrofrRufB70Jd3tOd/S38pQLX/5Er2S/NWFED1K1mML2XDHbFwvrMSWOxwjuxD2ecFsYZZJw4zq3E118XsPAZQi57uGGdg7PS1/mJsa9ngTfAQHx+bT8ePXmtSShkkuZX6ob2HGv91onG2+M8FZ56F239W3fGy0Dlc1yNjTwt/J1FabTpBe5Gv5OaNUp8XTrST6nN/dSVUKdnpafN6wI0blDNGrSRIrhOjWFo31sGishzUPreBXRaO55vRbURxQ33VJGTHrIZna+vm8EoCkatNK8mIlglqjgprhn1RYl3d4rA/IYIz2QQ3fVENloC0Pr9UGf1UdfwwqMPbt/dblgIaPy2MnAKa2ZnevqrYul/hhQ038x/ptrdUO4LViax9xjiXbPeC16ngNXV5l/ZlitTcUhZ9VRr+unbmrgwxYV4uK8VhVUJO+20Pm7j6YxG73WIljvOfB11XQWSXRlpTF7sHX2hpOEHq9ij4loZNHr776asI7POOMM9ocjBBChCwa6+EfF/4xvCgBHxJ7Za1PKqyZ1FPSrA+00AdeUFs3emIP1DZ+4M54Yh9Lfj4EM/QOGEoKG5KrKQuLImvFPrEHfj4Mkg+YlGRqq7fz3/sO/gEnaPxrpZSMSqKunzPylG9D7ENWVJOzo0ni9WYpjExuHL/Y9NgENTy2K7JW7DN74cYCqz5s08cabEh4n97TuC2A9dgvHBA1Frwm/LWxxFZyRYBJL5fwzTm54VJWgHUcDcXgFVUMXFVzUMenNSa+WkpVvou6LHtEkqSCGofH5NB/F3daLN3OE7ut53xSlOf8fj8sLOq8WFZUWeN0j8gMP1eAxtf3s3uhonO+RIruJaE6sYaRWIetUopgsGuKVSdC6sQK0TOseWiFtTgBYDMckDOk5RsprHJXs7NhoMv6gFtVDe+XRS3O7kkx+Oa8/pSMSA6fk0rb52PCa6XkbItymjTDblUhODLDSmYrA1byvKTMWjygE5nAmtP7sfvQtPAYX1d1kFEflFPwRVXzGzgUzMqyfvo5rOTyyypYXAbFUeprptoaHmumNfO7OmjVw/2gLLKmbMi4FDgnDwY4GwNcW2MlvFEWXygb6mbLzAyKx6SgDWuYQeGnlQz6pqbTFxjwuQ22HZXB9sPS8abZcNSbDFlRTeGnFSRVdd/Ps06R2fCcP6LJc/7jCviw85/zKGB6OszJhiFuK5ldU2M9h2MtwiF6rETrxCa82EFvIEmsEN1TqNcVYNSHq3G9sDJ2r2sHMOm5Y6t6cuzQWLO+O+hOsQjRlyWaxEp1AiFEl8p6bCHLTr81PFwAOi95DenJSWBPjh26V9LYnWIRQrSsTUlsbW0tH374ITt27MDnizwVdf3117dLYEKI3unpq/eGfw+XyaLzE1chhBA9W6uT2K+//ppTTjmFuro6amtryc7OprS0lOTkZPr37y9JrBAipqzHFrLh9FsjttkkeRVCCNEGrU5if/7zn3P66afz8MMPk5GRweeff47D4eB73/seP/vZzzoiRiFEJ7KnVJE9eTnOjHICtamUrZqOr+Lg1kl/+uq9bLhjNpwep8JAOwjaFXsnpFCV78IIaPI21JK509tup4krj0xHn9Yfm1MRqDdxvLCX1LV17bJvraB0RBKlI5LQSpG100Pe+trIKgmdKdNuTaRJt1tVCb6sij8DPN8FU9PAbViTxb6sAk9XBS+E6AtaPbErMzOTZcuWMWbMGDIzM/nss88YN24cy5Yt4/LLL2fDhg0dFetBk4ldQsSXN+sdBh23CJRGmwbKMEFpSpYdw843zgfduhGYoQlbExrKZHVkr2vJyCRWXJRHIMmGClild7RNkbWtnsOe2Yczyiz5RJl2qP39aFJdzR9/ZVWA9Fs3H9TY1LosO19clk9Nf2e4bqm2KVxVAQ57ai+Ze6JUEOhIp+fCCTnW701njr27HxaVRLZ1KLhsIExNtypCaMAG+DW8sA+WdU7dVyFE75HoxK5Wv+86HI5wya3+/fuzY4dVAzAjI4OdO3e2MVwhRFfrN/1jBp/4CspmogyNYQ+iDI1SkHv4Ugad8EpC+1nz0AqyHltoTdj6cBITfvoUNsPRoQlsZb6TL76fT6AhydR2Fa5BWjHEzbLL89EH0R1b89tRpLoMlFLNfjIzHJT/urDN+w44FJ9dMZDaHIcVu60xdl+qjc+vGEh9uq3twbfWCTlwUj+rFqehrKVFQ7+f1K8xuQ35fj5MTrN+tzW0V8pKbr+XD4fImvZCiI7R6uEEU6dOZfny5YwaNYrZs2fz61//mtLSUp566ikmTJjQETEKITqaESR/7usxl0tXCvof+QH7PjqRYH30pCS8OMH5T0Wcvu+MCVtbZmU2jFNoHry2KSoHuykZkUT/za2vJ1lb4CYt2YaKsUqW1prsXBcBN9jbsArn7imp1Gfaox54bSiCToNtR2Qw7p2y1u+8tRwKTsyJ3+bEHKs2rl9DnhMOzYjeTimrlucpubCutv1jFUL0ea3uif3d735Hfn4+AL/97W/Jysri6quvpqSkhL///e/tHqAQouOlDNqOM70q7nLphj1Ixug1EdtCS8Ie2Otq5A4P/3Q0rWDvhNTG1Z+iUEHN3ompbdp//fl5MRNYINwjW3HegDbtf8+EVOsUfAzaUOyZ1LbYW210irVCUzxJNqsdWCukxVqaFKwvFQVJ1kIRQgjRzlr9zjJ9+vTw7/379+ett95q14CEEJ3PcLa8PrzWYHNZ7Z6+ei/frP8Zv3phpXVlvCVhO5hpEDeBBSvRDTjbNmrVcBtoreMmsgD/v707j4+yvPc+/rlnskySSSYrgUASVkFAFBABRQGLijyNYmtUzqmCD3rOo1hrXY5Y8aD1eDwWejxWWotiC4V6qFhFoXVnEREjWxAsWxAMQgIhy2SBbDP388ckQ0IWkpBkMpnv+/Wal87MnXt+s5B8c+W6fheRbQtq1TZL0/vC1x7TyFzcDmFr4ePUHhdqaTaA1zteU2NFpJ21+dfjkydPsn//fgCGDBlCQkJCuxUlIp2rIv/8/34NA8rzEuu1yeoK7bGsLrA5qymPsjY+F6KG/VTbFke5vi/HSLSd97igPSVtOn/kyUqKe4U2HcTdJva8TlrYdeL8v8zUO+5kpWcRV3Oq3FBYdUFliYg0ptW/3peUlHDnnXfSu3dvJk6cyMSJE0lKSuInP/kJTqd+1RbxR5VF8RRnDcZ0NfEtwQSraeXBjDTmpD2JQdcIsLX6fuk874hg8va2hcy45Tm4TZOmGrmYpkml2yR6U9u+/6VsLW5+JNli0PfL4jadu9W+r4DsM01PEXCZnvu/rwmxO4qhwu2Z+9rU8V85oTJgdjcXkU7U6hB7zz33kJGRwdq1aykqKqKoqIi1a9eybds2/vVf/7UjahSRTpC95g5cFbYGQdZwubFUuxiz4Esspie8drXdtfptcRJ9rKJhmKq5PvSDfMKb63HaDEs1FHxZBNAgyNZeL3v3RJvODRCbXUHfzZ7z16vfNME0SfxHKUm7S9t8/lb7cw5Umw2DrMv03P7nszuuUVnn+rmvvcv0jMCe25JLRKSdtLpPbEREBB9++CETJkyod/umTZuYOnUqZWVddxWq+sSKNO/9B/7B1MiNjAr/BgsmuE167Mln8KYzODq7V2krVQcbHJwcw3dXRFFdszgp6ngFAzcWkrTnwr8vFUyPJ2JyHCEWz0Iu0zQprzapeDu3zaOwtUwge0wkh66O4XRNq63Qkmr6feGk/+dFnb/hQc8Q+D8JMCLS0zbLZcLXJfC3PMht5HNwUTjcGA+DahZ8Vbo9/WH/lgelrs6tXUT8Xkv7xLZ6TmxcXBwOR8OWKg6Hg5iYmNaeTkS6AG97rJpNCapDrVRGhRBq602In+y6FFRlcvFHBQz+tIDyqCAs1Sa2kvYLULGrT8HqU5T1tVGVHIrtYBlhudWEtcO5DSB1awkpW0sod1gxDYMwZzWGr/4Kn1sJrx/zLMiyWz1BtLnPwYHTcCDbc2yoxbPDV5WmEIhIx2p1iJ03bx4PP/wwy5cvp2dPT0uZ3NxcHnvsMZ566ql2L1BEOlbMklVkpD0JG8FqCYa4ZKxAKPjltqEWF4QXtm3qQEtEHCmHI21oCNsCBhDm7EIjl+Xu1n0GSl0aeRWRTtPqEPvKK6+QlZVFSkoKKSkpAGRnZxMaGkpeXh6LFy/2Hrtjx452K/S5557jb3/7G5mZmYSEhFBUVNRu5xYJRLVtskLTMn3WHktERKStWh1ip0+f3gFlnF9lZSXp6emMHz+e119/3Sc1iPi7mCWrvP/fldpkiYiItFarQ+z8+fM7oo7zeuaZZwBYunSpTx5fxJ+dO+payx9GX0vjg8nv5+nTGne4HPup9us56rbAqYHhnI4JIviMmx77ywiuaHoupyvY4MTgcCojrNic1fQ4eBqLL/96nmyDVJtn4dW+MujAaRQiXUKKzXNxmbC3DNrYdUS6hzZtdlBUVMRbb73FoUOHeOyxx4iNjWXHjh0kJibSu3fv9q6xzSoqKqioONu8u7i4k3otinQBa4Z45m3WXbDlT6OuFRFWdqb34NSgcE+7KQDDID7rNJetOontAudenhgcztfTE6iICvKc3zCwVLoZtLGQgRuKOLdz6+FxUey7Pg5XqMV7fEiZi+Fr8kja3cldWRKCYVZvSA3z1oLb9PRtfSNHfVml++kRArOSIOWcz/z2YvhffeYDVatD7Ndff82UKVNwOBwcOXKEe++9l9jYWN5++22ys7P505/+1BF1tsnzzz/vHcEVCRR7Fm1nZfoM5tW2Lq2zYMtfuIINttyTRFlNu6m6O3Hl9wtjyz1JXP3b7wlq4wr4U/3D2PqTnmdvqDm/O8TC/uviMC0GF60r9N59eFwU36QlNDi+MtzCjjt6Yrhy6fWPTgqykVb4eV+IsNarBYsBo6IgKghezm7ZdrAi/sARBD9PhfBGPvOjaz7zi/SZD0St3uzg4YcfZtasWRw8eBCb7exWjNOmTeOzzz5r1bnmzp2LYRjNXvbt29faEr2eeOIJnE6n93L06NE2n0ukq1szpJzp859lZfoM745atRd/CrAA319mpzQhuNGdrEyrQVl8MMdGRrb5/HtviPX8j6XxnbIOToyhMszz7dEVbLD/urjGT2QYYJrsnRrXeT8/J8d6Amxju3xZDLgoAoZEdFY1Ih1vUownwDb1mR8c4blIwGn1SOzWrVvrdSCo1bt3b3Jzc1t1rkceeYRZs2Y1e0z//m3/82doaCihoaFt/nqRrm7Pou1cbfsWoEGbLH92dFSUZ1Slqd1YTTg6KpLUr1o/RagsNghnH1uzx5hWyBkWQeq2Ek5eFE61rZnf9w2D03HBOHuHenYN62jjohv/YV7LZcIYh2e+oEh30KLPfJRnXrgElFaH2NDQ0Ebnlh44cICEhIRGvqJpCQkJrf4aEamzUCvd/xZqtUSl3drkKCkAFoMKu7Vt5444/9cZ7rPHVUZYz87Ba0ZFC87bLsLP8zhWA6I6qRaRztCSz3xkm5b4iJ9r9bt+00038ctf/pI333wTAMMwyM7O5vHHH+fHP/5xuxdYKzs7m4KCArKzs3G5XGRmZgIwcOBA7HZ7hz2uSFcTs2RVt2+PFVZYxenooKaDrNskvLBtXQpszvOvZjYtEFaz6tnmrD5vgIWzx3c4ZxXEBjddk8uEAq3Ylm7EWQ0xQef5zLdf1xLxH62eE/vrX/+a0tJSevTowZkzZ5g4cSIDBw4kMjKS5557riNqBODf//3fGTlyJPPnz6e0tJSRI0cycuRItm3b1mGPKdKVrLgvh8cm3cactCe9c167q5StJecdiU3ZWtKmc4cVu4g/eBrD1cQsVtPEWmnSs2ahVsLB04SUVp/tkHAut0nUsQqiTla2qZ5W21zU/AIWqwFbijqnFpHOsLlQn3lplGGaTX1nbt7mzZvZtWsXpaWljBo1iilTprR3be2uuLgYh8PB3NuKsAVH+bockfOaPv9ZBm3cDUDoXzKB7h1ea7ktkHF3L/L7hjUMs26T2O/KGfeH41jauCtucc8QNv9rb1xBRv3z10wbGPH2SVK2nw3JOcMi2D4j0fODtO7xbhPDDeNfP05sdsdsRduAzQKP9oWEkIbzBE0TtjrhTzmdU4tIZ7BZ4LG+EN/EZ/4rJyzXZ747Ka6qxvHWOpxOJ1FRTee1NodYf6QQK/6itk0WeNY2WSw1rab8fMFWa7iCDfbeEEf25ZG4gz1/NLJUuUneXsLQD/KxtrG9Vi1nrxD2/DCewr5h3tvCCqsY8lEBvb8ubXD8iSHh/GNqHGUJId7bHN+XM+xv+Z0XYGtFWOHWRE9Lrdof6mdcsKEA3j8FbQz3Il2WveYzP/Kcz/z6ms98wCSZwNDuIXbLli3k5+fzwx/+0Hvbn/70J+bPn09ZWRnTp0/n5Zdf7tLdABRipataM6Scfg98A8C8vL8z/P7lnvAaAKOu51MVasHZ2/N9xXG8guDy9k1opXHBnI4JIuSMG8fxCoxmviOaQHGvECoirIQ5q4nM8/E8PLsV+tig2oTvzsAFBnuRLi/SCr31me/uWhpiW7yw65e//CWTJk3yhtjdu3cze/ZsZs2axcUXX8yCBQtISkri6aefvuDiRQLJnkXbyUifARvP3tYd2mS1l+AKN/Hfnumw89vzq7DntyyMGoAjp5PmvrZEqUtthSSwlOgzL2e1OMRmZmby7LPPeq+vXLmSsWPH8tprrwGQnJzM/PnzFWJFWujcNlkadRUREWm5FofYwsJCEhMTvdc3btzIjTfe6L0+ZswY7Yglch4xS1Yxp6Y91rynPbcFwkItERGR9tbiEJuYmMjhw4dJTk6msrKSHTt28Mwzz3jvLykpITg4uEOKFPF33lHXtCZGXYMNSLFBkAHHKjx/Jm5HZxxWSuNDsFa5if6+os2r+n2hKtSCMykEDAPHsQqCK5ovvjzSSkmPECzVJtHfl2M930uZEAxxIXDaBUfLtUCkhgmUXWKnOiGYoLwqInaXNrmBWpcUHQQ9Q6HC7Zk76UefeRFpmRaH2GnTpjF37lxeeOEFVq9eTXh4OFdffbX3/q+//poBAwZ0SJEi/ihmySoAJh7dx7z7lwONjLoawNR4uDYWwmp2pXGZsKMY3joBZRcWZk9HB7EnLZ6Tg8O9jcJDSqsZtL6Qvl8Wd+lQ4goy2Du15d0JyiOt7PlhPLlDI7xtsIJPuxjwWREDPi9quGCrdyjc1hMGhJ+97VQlvHcSdrStB2134ZwYgzUtAbvt7E5JpeUuXGvycGws9GFlLRAX7Hlfh0acbY5fXA0fnILPunjtItIqLQ6xzz77LD/60Y+YOHEidrudZcuWERJyttXMH/7wB66//voOKVLEn3jbY6XhDYmWphZq/VMvGOeovxON1fC0Tkq2wcIj0MbV+GeirHz+/3pTFW6td/5KexDfpCVQGWFl8Kdd84e62wJf3dWT/H71+8S6gy18d0UUJT1CGPfHs31iK8MtbP7X3pRH1d/lqyrcyr6pcZRHWRn+t/yzD5AUCg/39Yx81xUXDP+3D4Qchy+dHfgMu66iyTFE/SixwS84EaEWzFsTKbJA9Pqu+bkhOgge6etpQVb331RUkCfY2q3w91M+K09E2leLQ2x8fDyfffYZTqcTu92O1Vp/L+NVq1Zp+1cJaGuGlPP67QuYl97C9lipNhgf3fh9VgN6hMA1MfBRfuPHnEfWpBiqwq2Y5zYHr3FwUgwp20oIa8E2rJ0td1gE+XVHSOuyGBT0DyNnuN3bz/XQhGjKHUGYTezydeTKaFK/Kj7bEuuWHp4Ae+5rYxie5um3JnpGwysDa26BCYTc1AMDz5bidRk1r03ITT0w1xd2zVH8qfGeANvEZ56p8fBFEXTWFsEi0qFave2sw+FoEGABYmNj643MigSSPYu2k7FxBMPvX47VEtyyTgPjoz1TB5piABNi2lSP2wpHR0U2GWBrHR0V2abzd7TvxkSBu5nXxm2SPcZTuwlkj4lqMsACGC6To6Nreg1GB8HF9qaDjmFAqAUu7ZqvTUcqGe8gPNjSIMDWMgyD8GALJeMdnVxZCwQZMNbR9Ptaa2wXrF1E2qTFI7EiclbtQq1abWqTFRvc/A9cwwBH2/6JVtms3nmkTZ7ehDNtPH9HOxMT3HC72bosBqdjPAtJ3UGGZ8pEM0wDzkTXPNfoFjxnNxATeAtVq3u2bLOalh7XqcKtcJ7PfKC+ryLdVdf8CSbShcUsWcW+mjZZ1trtYNvSJqvU5RmJbS7Inm7bwq6gCjeGyzzvSGzoBS4c6yghpS5ORwc1HWTdJqE1HRws1SaWSjfukKYDjGFCSO1zbUnnB0sLj+tmLEUt2/Shpcd1qjMt+PdkEJDvq0h3pRArch4r7svhsmHHAVj21gtNt8lqra1OuKKZP226zDYvLrJWm/T6ppScYfYmg6xpNei9q2uuwk/eUUJRcjOjfQb0qekgYAB9Mks4Ojqq2efaJ7PmuZ6q8rRcSrY1HZJdJnTR16YjRW0qpGJ6IiGWhnNiAUzTpNLtOa7Lqap5zy6NbDrIWg3PvzsR6RYUYkWaUXfUtVa7bU6wrwz2l8Gg8IZhymV6RmE3FLT59IPWF3JiSAQug4bnd5v0ySwh8mQXHFHDE0oPX+mgLC64QTA1XCbhBVVnQykw8LMijo+wU42lYYBxmyTuKyP6aMXZ2949CQ+keObdNhZkP8y/4PZm/shSDWWbCgidFIdpmvWCbO310s8LiOuq66LePwXD7Z7fbBr5zJPhhBNdaNtgEbkgrV7YJRII9izazrwTFzEn7UkMPMG19tJuTGDxUc8qeLfpWRVv1ixmOl4BL34HF9A5IPJkFeNeP054QU1QrTm34TJJzShmxDt5F/gEOo61ymT8kuPEHT7juaHOaxN75AzjlxwnqE7ngPDCaq589Tj2U/WfK26TPjtLGPWXk/VX0x84DYu/h5Lq+sdXumHNSU8YClCxb50k//MCqmteErPmtak2IX9zAXGrTviwuvPIqYDffAf553wOXKanR+z/5viuNhFpd4ZZ+x0qABQXF+NwOJh7WxG24ChflyNdSG17rEEbdwMQ+pd2mjLQUjFBMMTuWWGdfQa+K2+3U5tAfj8bpT1CsFaa9DhwusvOhW1MSUIwBX3DAE+A9bbJaoQJFKaEUtwrFEu157naSpp5rhZgSATE1+zYtae0zX15uxuXzULxdbG4YoKxFlYR9XEBVn96bQaFQ6+aHbu+KdVcWBE/UlxVjeOtdTidTqKims5rCrES8LybE1BnoVZjGxOIiIhIh2tpiNWcWAlYtW2y2tQeS0RERHxKIVYCyor7PHPifjr687NtshReRURE/I5CrASE2lHXeU9nem/rSqOvJlARacVtNbAVV2Pxo6mHHc1tAWeSZzdAx/FKvTYiIgIoxEoAqLc5QRcJrXUdG2Hn4KQYShM9QS2kzEXql04GflaEtTpgpqw34LbAjtsTyb044mzbLLdJ4t4yRq88oTArIhLgFGKl29mzaDvz8v4OwPD7l0Na1xp1revA5BgOTIn1tNiqURlh5eDkGAr62Ri7NAdLAC6qdgMbfpbM6bhztgg14MTQCNY/lMLk/85Wj0ARkQCmECvdRm2brHnpy4GaTgOW4C7baaAkIdgTYKFhY3aLQX6/MLIvj6JvRnHnF+djWZOiOR0f0vCOmub7Z+KCOTg5hsHru+DOUSIi0ikUYsWv1d0SNiN9BmysCa9dNLjWlX15FIbLbHKrVIAj4xwBGWKPjHV4GtU3svUpAKbJd2OjFGJFRAKYQqz4Je+o6/3Lvbd11SkDTSlNaLilaj2GQdm5f04PEFUR1qYDLIBhUBVu7byCRESky1GIFb8Ts2QVGWlP+tWoa2OCKk3PXNhzpxLUYa0KzNVLhsvEtNDsSKzhDtxFbyIiohArfqC2PVat0LTusTlBrz2l5Fxib/J+w2WS9HVpJ1bUdcQdPkPeReHnPUZERAKXQqx0afXaY9VuCevn4bVWz3+UYT9ZSVlcI9MK3J6Rxv6bnb4pzseGrT3Fhp+nAI3Mi63ZKXvY2lOdX5iIiHQZ6lAjXdKeRduZd+Ii5qQ9iUFNf9e4ZL+dOtAYixvG/eE4kbkVgGfk1ajpCxt8xs3YpTnYT1X5skSfsRdUc/nyHIza2RSm6Q2vhhsuX5GLPb/adwWKiIjPaSRWuoQ1Q8pxTvasNH+rx5KzbbK6yahrU2wlLq7+3TEK+to4eVE4bqtB9LEKen5TijUA+8PW1fPAGW58+lsOTorh5GDP1IIeB08zaF2hNjoQERGFWPG9PYu2e9tj1fLnBVutZQBxR8qJO1Lu61K6HIsbBq8rZPA6tdISEZH6FGLFZ9YMKeeznncRmt49FmqJiIhI51GIlU4Vs2QVE4/uA/D2eA2kUVcRERFpHwqx0ilq22TVtseqpdFXERERaQuFWOkwK+7LAeCnoz8/2yarA0KrCewbegk7x4zjRM9eWEyTvocOcnnGF/T+PrvdH8+XTCB3aATfXuWgKNkGJsQfOs2Az53Ef9v9+qaeuCicw1c5yO8bBgbEHjlD/81OEvef9nVp3VpFuIXDV0WTPTqSyggrIWUuUraX0G9zEaGntapORLoGwzTNgNn2pri4GIfDwdzbirAFR/m6nG5rxX057Ht6Yr3bOmrOqwl8cmMau0dejuF2Y1o8XeMMlwvTYuH6v73L8K93tvvj+oIJ7J0ax7dXR9fb6ctwmZhWg6FrT9F/S/fpK3twUjT7r4vzPj8Aw21iWgwu+qSAi9ZrsVdHOOMIYvO/9KY8ylp/Nzm3ia3ExVWLvyfMGeCtM0SkQxVXVeN4ax1Op5OoqKbzmvrESrtZM6Sc6fOf9QZYa0J/76Wjpg0cuHgYu0deDuANsACm1QrAx9NuwumI7pDH7mynBoZ5AizUCxe1Ae8fP4ynODHEB5W1v8LkUPZfFwdQbyMIs+Z5H5gSS0FKqE9q6+52/SiBikhrw+2QLQYVdiu7ftTDN4WJiJxDIVbaxZ5F28nYOILh9y/HagnutP6uOy8fh+Fu4s+bNTs97b5sdKfU0tEOj3dguJr+w4nhMvlubPf4C8ORsed/rkfGOTqxosBQGhfMqYHhDXeQq2FaDU4NDKc0LriTKxMRaUhzYqVN1gwp565H1wBwz4pVPmuTdaJnr3ojsOcyLRZyk3p3YkUdp6hPaJPhAjwBo7CPrRMr6jiFKS14rsnd47l2JcVJLRvJL04KwZ4fmLvJiUjXoRArrRazZBUZaU/CRrydBiw+apNldbtw0cyokOnG6uoe8/cs53sapomlmdFLf2JpwY6y1uru8Vy7EqOF/1RaepyISEdSiJXzWjPEs5OUc3JhvTZZXaE9Vv+DB9h/8TDvHNiGDPpnHejUmjpK4t4yssdENT1CaULPvWWdW1QH6bm3jKyE4IbzMmu5TRK7yXPtSuK+PYOl2o07qOm/bliq3cR1w04YIuJ/FGKlWd5RV/BuC9tZ811bYvRXX7B/6HAwTe8c2FqG243tzGku3rPLR9W1r35bnGRfHlWvM4GX2ySo0k3ytmLfFNfOUr9y8u2VDtxBNPpcLdUmqV91j+falYSUu0nJKObIeEfjv0C4TVIyigkpV5stEfE9LeySRq24L4d5Jy5iTtqTGNTvNNCVJObmMO3dt7C43Z4FXqYJNf+1nTnNrf/7J0IqK31dZruwn6ri8jdyPVMG3GbNc/X8N6jCzdilOd2mh2eY08UVf8rBWlX/eWKaWKtMrlieS3hRC+YcSKsN/TCfnv/wjHLXLq6r/W/PvWUM/TDfZ7WJiNSlPrECeKYMvH77Au/14bVbwnax0NqU0gg7ey4bTW6vJCxuN32/zeLib74muKr7LT6pCLdwdHQUhak2ME0Sss7QO7OE4Iru90+50mbh+1GR5PcLAyDuyBn6bC/RSGAHM4HCFBtHR0VSHmXFVuIieUcJMd+V0/RyOxGR9tHSPrEKscKeRdtZmT4D8P1CLREREQlsLQ2xmhMbwGpHX+elL+8yC7VEREREWkIhNkDVbZNl1airiIiI+BmF2ACx4r4cT3usv2R6bkhDo68iIiLitxRiA0DMklXsq2mT5S8LtUQCzemBYZy5uQe23jYMA86crCTk/TwiM0sv+NymAScvCue7K6Io6RFCcLmb3rtKSd6mdlki4r8UYruhFffl8NPRnwMwJ+1JjbqKdHGF0+Jw3JiADbDU9Du2JYVizO5D/ldO4pbntPncpgE703tw/NJIDJeJaTU4Y5oU94zl2wkOxr92XFvIiohfUojtRrwLtWraY3k7DSi8inRZ5Sk2HDcmYABGnQ07asNs3Nhoig+UEZXRts0dvr0qmuMj7ABnd3szDDCgMtzK1jt7MumloxgB06dGRLoLv9js4MiRI8yePZt+/foRFhbGgAEDmD9/PpXdpIn9hVgzpJw1Q8rZs2g7GRtHMPz+5VgtwVgT+mOpuYhI11U6PQGoH2Drcpsm1TfEt+ncpgHfXuVo+n6rQVlCCKf6h7Xp/CIivuQXI7H79u3D7XazePFiBg4cyJ49e7j33nspKytj4cKFvi7PJ84ddWWjpgyI+KOQ3jbvqGtjLIaBPS6kTec+HRNERVTz3+YNl0l+/zASDp1p02OIiPiKX4TYqVOnMnXqVO/1/v37s3//fl555ZWADLF7Fm0nI32G2mOJiIhIwPKLENsYp9NJbGxss8dUVFRQUVHhvV5c3LY5Zb5Wd6HWPStWEZqeqVFXkW6i8lg57kERTY7Guk2T0vxKmv9u17jwwmpCi6upiLR65sE2wrQaxB3WKKyI+B+/DLFZWVm8/PLL5x2Fff7553nmmWc6qaqOUbc9lhZqiXQ/9tV58FgEpmk2Oi/WYhgEfXiqTec2TOj3hZN9NzQegQ2XSXhBFfGaSiAifsinC7vmzp2LYRjNXvbt21fva44dO8bUqVNJT0/n3nvvbfb8TzzxBE6n03s5evRoRz6ddrXivhwem3Qbc9KexAAt1BLppmzZ5Tjfz8PEM+pay22amKZJfkZRmzsTAAz4vIheuz29Zg1XzflNE9wmIaddjFmeq84EIuKXDNM0ffbtKy8vj/z8/GaP6d+/PyEhnkUNx48fZ9KkSYwbN46lS5disbQugxcXF+NwOJh7WxG24Kg2192RahdsDa9ZsKXNCUQCQ4dvdjA4nO/G1N3soITk7SWEnNFmByLStRRXVeN4ax1Op5OoqKbzmk9DbGscO3aMyZMnM3r0aFasWIHVam31ObpqiN2zaDvL3noBwLstrBZsiYiISCBqaYj1izmxx44dY9KkSaSmprJw4ULy8vK89/Xs2dOHlV0Yb5us9OWehVqWYFB4FRERETkvvwixH3/8MVlZWWRlZdGnT5969/nJQLLXnkXbAbja9i0ZaU+qTZaIiIhIG/hFiJ01axazZs3ydRkXZMV9Oeza+zNC0zO9t6lNloiIiEjb+EWI9Xd122RpoZaIiIjIhVOI7QDeUdeaRVqkadRVREREpD0pxLaz6fOfZZ7aY4mIiIh0KIXYdrJn0XZWps+A+zXqKiIiItLRFGLbaM2QcpyTCwF4q8eSs22yFF5FREREOpxCbBvsWbSdjPQZsPHsbWqTJSIiItJ5FGJboW6bLI26ioiIiPiOQux5xCxZxT0rVgEw7+lMQAu2RERERHxNIbYJ3lHXtExtCSsiIiLSxSjE1lG7Jey8vL+rTZaIiIhIF6YQS532WOlnb9OcVxEREZGuK6BD7Joh5bx++wK1xxIRERHxMwEZYn82YSYJ733DvBPARrXHEhEREfE3ARlibW/vxtproK/LEBEREZE2CsgQa4nv6+sSRNrMbYETQyIoTLWB2yT+0BkSDp3BMH1dmYiISOcJyBAr4q+cSSFs/Ukvyh1BGC5Pav32mhjsJysZszyHiIJqH1coIiLSOSy+LkBEWuZMlJUt/zeJikgrAKbVwLQaAJTFBbNldhLVIYYvSxQREek0CrEifuK7sQ6qQy2YloZB1bQalDuC+P6ySB9UJiIi0vkUYkX8xPERdmgkwHqZcPwSe+cVJCIi4kMKsSJ+ojr0PP9cLQbVNv2TFhGRwKCfeCJ+wn6yEtxNtyAwXCaRJyo7sSIRERHfUYgV8ROpGcXNTicwrQapW4s7sSIRERHfUYgV8RNJe0rp+U0pmKbnUqtmdLbvF0XEflfuo+pEREQ6l0KsiJ8wTBi18gRDPiwgtMTlvT28sJpLVucx7G/5PqxORESkc2mzAxE/YnHDwE1FDPi8iPKoIDBNbMUu1B1WREQCjUKsiB8yTAhzancuEREJXJpOICIiIiJ+RyFWRERERPyOQqyIiIiI+B2FWBERERHxOwqxIiIiIuJ3FGJFRERExO8oxIqIiIiI31GIFRERERG/oxArIiIiIn5HIVZERERE/I5CrIiIiIj4HYVYEREREfE7CrEiIiIi4ncUYkVERETE7yjEioiIiIjfUYgVEREREb+jECsiIiIifkchVkRERET8jkKsiIiIiPgdhVgRERER8TsKsSIiIiLidxRiRURERMTvKMSKiIiIiN9RiBURERERv+M3Ifamm24iJSUFm81Gr169uPPOOzl+/LivyxIRERERH/CbEDt58mTefPNN9u/fz1//+lcOHTrErbfe6uuyRERERMQHgnxdQEv9/Oc/9/5/amoqc+fOZfr06VRVVREcHOzDykRERESks/lNiK2roKCAP//5z1x55ZXNBtiKigoqKiq814uLizujPBERERHpYH4znQDg8ccfJyIigri4OLKzs3n33XebPf7555/H4XB4L8nJyZ1UqYiIiIh0JJ+G2Llz52IYRrOXffv2eY9/7LHH2LlzJx999BFWq5W77roL0zSbPP8TTzyB0+n0Xo4ePdoZT0tEREREOphhNpcCO1heXh75+fnNHtO/f39CQkIa3P7999+TnJzMF198wfjx41v0eMXFxTgcDpy3XktUsF/OpBARERHp1oqrqnG8tQ6n00lUVFSTx/k0ySUkJJCQkNCmr3W73QD15ryKiIiISGDwi+HIjIwMtm7dyoQJE4iJieHQoUM89dRTDBgwoMWjsCIiIiLSffjFwq7w8HDefvttfvCDHzB48GBmz57NiBEj2LhxI6Ghob4uT0REREQ6mV+MxF5yySWsW7fO12WIiIiISBfhFyOxIiIiIiJ1KcSKiIiIiN9RiBURERERv6MQKyIiIiJ+RyFWRERERPyOQqyIiIiI+B2FWBERERHxOwqxIiIiIuJ3FGJFRERExO8oxIqIiIiI31GIFRERERG/oxArIiIiIn5HIVZERERE/I5CrIiIiIj4HYVYEREREfE7CrEiIiIi4ncUYkVERETE7yjEioiIiIjfUYgVEREREb8T5OsCOpNpmgAUV1X7uBIRERERaUxtTqvNbU0JqBBbUlICQPK7n/m4EhERERFpTklJCQ6Ho8n7DfN8MbcbcbvdHD9+nMjISAzD8HU53UJxcTHJyckcPXqUqKgoX5cTkPQedA16H3xP70HXoPfB9/z9PTBNk5KSEpKSkrBYmp75GlAjsRaLhT59+vi6jG4pKirKL/+hdCd6D7oGvQ++p/ega9D74Hv+/B40NwJbSwu7RERERMTvKMSKiIiIiN9RiJULEhoayvz58wkNDfV1KQFL70HXoPfB9/QedA16H3wvUN6DgFrYJSIiIiLdg0ZiRURERMTvKMSKiIiIiN9RiBURERERv6MQKyIiIiJ+RyFW2sWRI0eYPXs2/fr1IywsjAEDBjB//nwqKyt9XVpAee6557jyyisJDw8nOjra1+UEjN/+9rf07dsXm83G2LFj+eqrr3xdUkD57LPPSEtLIykpCcMwWL16ta9LCjjPP/88Y8aMITIykh49ejB9+nT279/v67ICziuvvMKIESO8mxyMHz+e999/39dldRiFWGkX+/btw+12s3jxYr755htefPFFfv/73/OLX/zC16UFlMrKStLT07nvvvt8XUrA+Mtf/sLDDz/M/Pnz2bFjB5deeik33HADJ0+e9HVpAaOsrIxLL72U3/72t74uJWBt3LiROXPm8OWXX/Lxxx9TVVXF9ddfT1lZma9LCyh9+vThv/7rv9i+fTvbtm3j2muv5eabb+abb77xdWkdQi22pMMsWLCAV155hW+//dbXpQScpUuX8tBDD1FUVOTrUrq9sWPHMmbMGBYtWgSA2+0mOTmZn/70p8ydO9fH1QUewzB45513mD59uq9LCWh5eXn06NGDjRs3cs011/i6nIAWGxvLggULmD17tq9LaXcaiZUO43Q6iY2N9XUZIh2msrKS7du3M2XKFO9tFouFKVOmsGXLFh9WJuJbTqcTQD8DfMjlcrFy5UrKysoYP368r8vpEEG+LkC6p6ysLF5++WUWLlzo61JEOsypU6dwuVwkJibWuz0xMZF9+/b5qCoR33K73Tz00ENcddVVDB8+3NflBJzdu3czfvx4ysvLsdvtvPPOOwwdOtTXZXUIjcRKs+bOnYthGM1ezv1hfezYMaZOnUp6ejr33nuvjyrvPtryHoiI+MqcOXPYs2cPK1eu9HUpAWnw4MFkZmaSkZHBfffdx8yZM/nHP/7h67I6hEZipVmPPPIIs2bNavaY/v37e///+PHjTJ48mSuvvJJXX321g6sLDK19D6TzxMfHY7VaOXHiRL3bT5w4Qc+ePX1UlYjvPPDAA6xdu5bPPvuMPn36+LqcgBQSEsLAgQMBGD16NFu3buWll15i8eLFPq6s/SnESrMSEhJISEho0bHHjh1j8uTJjB49mj/+8Y9YLBrobw+teQ+kc4WEhDB69Gg+/fRT70Iit9vNp59+ygMPPODb4kQ6kWma/PSnP+Wdd95hw4YN9OvXz9clSQ23201FRYWvy+gQCrHSLo4dO8akSZNITU1l4cKF5OXlee/TiFTnyc7OpqCggOzsbFwuF5mZmQAMHDgQu93u2+K6qYcffpiZM2dy+eWXc8UVV/A///M/lJWVcffdd/u6tIBRWlpKVlaW9/rhw4fJzMwkNjaWlJQUH1YWOObMmcMbb7zBu+++S2RkJLm5uQA4HA7CwsJ8XF3geOKJJ7jxxhtJSUmhpKSEN954gw0bNvDhhx/6urQOoRZb0i6WLl3a5A9tfcQ6z6xZs1i2bFmD29evX8+kSZM6v6AAsWjRIhYsWEBubi6XXXYZv/nNbxg7dqyvywoYGzZsYPLkyQ1unzlzJkuXLu38ggKQYRiN3v7HP/7xvNOhpP3Mnj2bTz/9lJycHBwOByNGjODxxx/nuuuu83VpHUIhVkRERET8jiYtioiIiIjfUYgVEREREb+jECsiIiIifkchVkRERET8jkKsiIiIiPgdhVgRERER8TsKsSIiIiLidxRiRURERMTvKMSKSLdgGAarV6/2dRltMmvWLKZPn96mr73mmmt444032regdrR06VKio6M75dxPP/00l112WYc8Vq1Jkybx0EMPea+PGzeOv/71rx36mCLSOIVYEWmzvLw87rvvPlJSUggNDaVnz57ccMMNbN682delNXAhQbG9HDlyBMMwyMzMbJfzvffee5w4cYI77rjDe9uuXbu46aab6NGjBzabjb59+3L77bdz8uRJwLNFq2EYFBUVtUsNXcmjjz7Kp59+2qmPOW/ePObOnYvb7e7UxxURhVgRuQA//vGP2blzJ8uWLePAgQO89957TJo0ifz8fF+XFhB+85vfcPfdd2OxeL6V5+Xl8YMf/IDY2Fg+/PBD9u7dyx//+EeSkpIoKyvzcbVtV1lZ2aLj7HY7cXFxHVxNfTfeeCMlJSW8//77nfq4IqIQKyJtVFRUxKZNm3jhhReYPHkyqampXHHFFTzxxBPcdNNN9Y675557SEhIICoqimuvvZZdu3Z576/9E/DixYtJTk4mPDyc2267DafT6T1m69atXHfddcTHx+NwOJg4cSI7duxo1+ezZ88ebrzxRux2O4mJidx5552cOnXKe/+kSZN48MEH+bd/+zdiY2Pp2bMnTz/9dL1z7Nu3jwkTJmCz2Rg6dCiffPJJvWkO/fr1A2DkyJEYhsGkSZPqff3ChQvp1asXcXFxzJkzh6qqqibrzcvLY926daSlpXlv27x5M06nkyVLljBy5Ej69evH5MmTefHFF+nXrx9Hjhxh8uTJAMTExGAYBrNmzQLggw8+YMKECURHRxMXF8cPf/hDDh065D137Sjy22+/zeTJkwkPD+fSSy9ly5Yt9epaunQpKSkphIeHc8sttzT4hebQoUPcfPPNJCYmYrfbGTNmDJ988km9Y/r27cuzzz7LXXfdRVRUFP/yL//SonOfO53AMIwGl759+3rvP997XlZWxl133YXdbqdXr178+te/bvA+WK1Wpk2bxsqVK5t6q0SkgyjEikib2O127HY7q1evpqKiosnj0tPTOXnyJO+//z7bt29n1KhR/OAHP6CgoMB7TFZWFm+++SZr1qzhgw8+YOfOndx///3e+0tKSpg5cyaff/45X375JYMGDWLatGmUlJS0y3MpKiri2muvZeTIkWzbto0PPviAEydOcNttt9U7btmyZURERJCRkcGvfvUrfvnLX/Lxxx8D4HK5mD59OuHh4WRkZPDqq6/y5JNP1vv6r776CoBPPvmEnJwc3n77be9969ev59ChQ6xfv55ly5axdOlSli5d2mTNn3/+OeHh4Vx88cXe23r27El1dTXvvPMOpmk2+Jrk5GTv/M39+/eTk5PDSy+9BHgC28MPP8y2bdv49NNPsVgs3HLLLQ3+TP7kk0/y6KOPkpmZyUUXXcSMGTOorq4GICMjg9mzZ/PAAw+QmZnJ5MmT+Y//+I96X19aWsq0adP49NNP2blzJ1OnTiUtLY3s7Ox6xy1cuJBLL72UnTt38tRTT7Xo3OfKycnxXrKyshg4cCDXXHMN0LL3/LHHHmPjxo28++67fPTRR2zYsKHRX56uuOIKNm3a1GwtItIBTBGRNnrrrbfMmJgY02azmVdeeaX5xBNPmLt27fLev2nTJjMqKsosLy+v93UDBgwwFy9ebJqmac6fP9+0Wq3m999/773//fffNy0Wi5mTk9Po47pcLjMyMtJcs2aN9zbAfOedd5qsdebMmebNN9/c6H3PPvusef3119e77ejRoyZg7t+/3zRN05w4caI5YcKEeseMGTPGfPzxx701BwUF1av5448/rlfX4cOHTcDcuXNng9pSU1PN6upq723p6enm7bff3uTzefHFF83+/fs3uP0Xv/iFGRQUZMbGxppTp041f/WrX5m5ubne+9evX28CZmFhYZPnNk3TzMvLMwFz9+7d9WpfsmSJ95hvvvnGBMy9e/eapmmaM2bMMKdNm1bvPLfffrvpcDiafaxhw4aZL7/8svd6amqqOX369HrHtOTc8+fPNy+99NIG53e73eYtt9xijh492jx9+rRpmud/z0tKSsyQkBDzzTff9N6fn59vhoWFmT/72c/qfd27775rWiwW0+VyNfs8RaR9aSRWRNrsxz/+McePH+e9995j6tSpbNiwgVGjRnlHEHft2kVpaSlxcXHekVu73c7hw4fr/ak6JSWF3r17e6+PHz8et9vN/v37AThx4gT33nsvgwYNwuFwEBUVRWlpaYPRu7batWsX69evr1fjkCFDAOrVOWLEiHpf16tXL++Cqf3795OcnEzPnj29919xxRUtrmHYsGFYrdZGz92YM2fOYLPZGtz+3HPPkZuby+9//3uGDRvG73//e4YMGcLu3bubffyDBw8yY8YM+vfvT1RUlPfP7ue+xnVfg169egF469y7dy9jx46td/z48ePrXS8tLeXRRx/l4osvJjo6Grvdzt69exs8zuWXX17vekvO3ZRf/OIXbNmyhXfffZewsDDg/O/5oUOHqKysrPeYsbGxDB48uMH5w8LCcLvdzf5FQkTaX5CvCxAR/2az2bjuuuu47rrreOqpp7jnnnuYP38+s2bNorS0lF69erFhw4YGX9eatkszZ84kPz+fl156idTUVEJDQxk/fnyLF/ycT2lpKWlpabzwwgsN7qsNagDBwcH17jMMo91Wpbf23PHx8RQWFjZ6X1xcHOnp6aSnp/Of//mfjBw5koULF7Js2bImz5eWlkZqaiqvvfYaSUlJuN1uhg8f3uA1rlunYRgArXoNHn30UT7++GMWLlzIwIEDCQsL49Zbb23wOBERES0+Z3NWrFjBiy++yIYNG+r9onS+9zwrK6vFj1FQUEBERIQ3IItI51CIFZF2NXToUO9CplGjRpGbm0tQUFC9BTXnys7O5vjx4yQlJQHw5ZdfYrFYvKNemzdv5ne/+x3Tpk0D4OjRo/UW4FyoUaNG8de//pW+ffsSFNS2b4uDBw/m6NGjnDhxgsTERMCzIK2ukJAQwDN/9kKNHDmS3NxcCgsLiYmJafK4kJAQBgwY4O1O0FgN+fn57N+/n9dee42rr74a8My5ba2LL76YjIyMerd9+eWX9a5v3ryZWbNmccsttwCeMHnkyJF2Ofe5tmzZwj333MPixYsZN25cvfvO954PGDCA4OBgMjIySElJAaCwsJADBw4wceLEesfu2bOHkSNHnvc5iEj70nQCEWmT/Px8rr32WlasWMHXX3/N4cOHWbVqFb/61a+4+eabAZgyZQrjx49n+vTpfPTRRxw5coQvvviCJ598km3btnnPZbPZmDlzJrt27WLTpk08+OCD3Hbbbd4/zQ8aNIjly5ezd+9eMjIy+Od//uc2jXo5nU4yMzPrXY4ePcqcOXMoKChgxowZbN26lUOHDvHhhx9y9913tzhwXnfddQwYMICZM2fy9ddfs3nzZubNmwecHbHs0aMHYWFh3kVEdTswtNbIkSOJj4+v15N37dq1/OQnP2Ht2rUcOHCA/fv3s3DhQv7+979735PU1FQMw2Dt2rXk5eVRWlpKTEwMcXFxvPrqq2RlZbFu3ToefvjhVtf04IMP8sEHH7Bw4UIOHjzIokWL+OCDD+odM2jQIN5++20yMzPZtWsX//RP/9SikdyWnLuu3NxcbrnlFu644w5uuOEGcnNzyc3NJS8vD+C877ndbmf27Nk89thjrFu3jj179jBr1ixvO7O6Nm3axPXXX9/KV0tELpRCrIi0id1uZ+zYsbz44otcc801DB8+nKeeeop7772XRYsWAZ7w9ve//51rrrmGu+++m4suuog77riD7777zjtaCTBw4EB+9KMfMW3aNK6//npGjBjB7373O+/9r7/+OoWFhYwaNYo777yTBx98kB49erS65g0bNjBy5Mh6l2eeeYakpCQ2b96My+Xi+uuv55JLLuGhhx4iOjq60dDSGKvVyurVqyktLWXMmDHcc8893u4EtXNXg4KC+M1vfsPixYtJSkryBsu2sFqt3H333fz5z3/23jZ06FDCw8N55JFHuOyyyxg3bhxvvvkmS5Ys4c477wSgd+/ePPPMM8ydO5fExEQeeOABLBYLK1euZPv27QwfPpyf//znLFiwoNU1jRs3jtdee42XXnqJSy+9lI8++sgb5Gv993//NzExMVx55ZWkpaVxww03MGrUqHY5d1379u3jxIkTLFu2jF69enkvY8aMAWjRe75gwQKuvvpq0tLSmDJlChMmTGD06NH1HufYsWN88cUX3H333a19uUTkAhmm2UgfFhGRTvL000+zevXqdtvFqivZvHkzEyZMICsriwEDBrT7+XNzcxk2bBg7duwgNTW13c8v5/f4449TWFjIq6++6utSRAKO5sSKiLSTd955B7vdzqBBg8jKyuJnP/sZV111VYcEWPD0hX399dfJzs5WiPWRHj16tGnqhYhcOIVYEZF2UlJSwuOPP052djbx8fFMmTKl0V2e2tP06dM79PzSvEceecTXJYgELE0nEBERERG/o4VdIiIiIuJ3FGJFRERExO8oxIqIiIiI31GIFRERERG/oxArIiIiIn5HIVZERERE/I5CrIiIiIj4HYVYEREREfE7/x8m4bFtudC3lQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 导入 numpy 和 matplotlib 库\n",
    "# 提示: 使用 import 语句\n",
    "\n",
    "# 定义决策边界的范围\n",
    "# 提示: 计算 X 数据的最小值和最大值，并适当扩展这个范围\n",
    "\n",
    "# 生成网格数据\n",
    "# 提示: 使用 numpy 的 meshgrid 函数结合 arange 方法生成网格点坐标 xx 和 yy\n",
    "\n",
    "# 使用感知器模型进行预测\n",
    "# 提示: 对网格点坐标进行预测，使用感知器模型的 predict 方法\n",
    "# 提示: 需要将 xx 和 yy 平展为一维数组，然后使用 numpy 的 c_ 方法组合它们，最后将预测结果重塑为 xx 的形状\n",
    "\n",
    "# 绘制决策边界和数据点\n",
    "# 提示: 使用 matplotlib 的 figure 方法设置图形大小\n",
    "# 使用 contourf 方法绘制决策边界\n",
    "# 使用 scatter 方法绘制数据点\n",
    "# 设置合适的颜色映射（cmap）以区分不同的类别\n",
    "\n",
    "# 添加坐标轴标签、标题和显示图形\n",
    "# 提示: 使用 xlabel, ylabel, title 方法设置坐标轴标签和标题\n",
    "# 使用 plt.show 方法显示图形\n"
   ]
  }
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